Libraries¶
In [1]:
# Import necessary libraries
import time # Time-related functions
import glob # Used to return all file paths that match a specific pattern
import numpy as np # Data analysis and manippulation
import pandas as pd # Data analysis and manippulation
import matplotlib.pyplot as plt # Data visualization
from datetime import datetime, date # Working with date and time
from statsmodels.tsa.stattools import adfuller # Test if time series is stationary or not
from statsmodels.tsa.arima.model import ARIMA # Forecast Model
from sklearn.metrics import mean_squared_error, mean_absolute_error, mean_absolute_percentage_error, root_mean_squared_error # For evaluation metric
from statsmodels.graphics.tsaplots import month_plot, quarter_plot, plot_acf, plot_pacf # For data explaration
from statsmodels.tsa.seasonal import seasonal_decompose # For data explaration
from statsmodels.tsa.holtwinters import SimpleExpSmoothing, ExponentialSmoothing # For HW model
from sklearn.model_selection import ParameterGrid # Library For Grid Search
from prophet.diagnostics import cross_validation # Library For Cross Validation
from prophet.diagnostics import performance_metrics # For evaluation metric
from prophet import Prophet # For Prophet Model
from pmdarima import auto_arima, ARIMA, model_selection # For Arima Model
import xgboost as xgb # For XGBoost model
import itertools # For XGBoost model
from sklearn.model_selection import TimeSeriesSplit # For XGBoost model
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\tqdm\auto.py:21: TqdmWarning: IProgress not found. Please update jupyter and ipywidgets. See https://ipywidgets.readthedocs.io/en/stable/user_install.html from .autonotebook import tqdm as notebook_tqdm Importing plotly failed. Interactive plots will not work.
Functions¶
In [2]:
# ----------------------------------------
# Function to plot model outputs
# ----------------------------------------
def plot_chart(data=None, train=None, test=None, predictions=None, title=None):
# Set the figure size
plt.figure(figsize=(10, 4))
# Plot the full dataset if provided
if data is not None:
plt.plot(data['y'], label='Data')
# Plot the training dataset if provided
if train is not None:
plt.plot(train['y'], label='Train')
# Plot the test dataset if provided
if test is not None:
plt.plot(test['y'], label='Test')
# Plot the predictions if provided
if predictions is not None:
plt.plot(predictions, label='Predictions')
# Add a title to the plot if provided
if title:
plt.title(title)
# Display the legend
plt.legend()
# Show the plot
plt.show()
Config¶
In [3]:
# ----------------------------------------
# Config Settings
# ----------------------------------------
# This config file stores adjustable settings (paths, options) used by the script.
# Input file paths (Data)
path = "C:/Users/WilcoxJo/OneDrive - DVLA/Desktop/Independent Project (ACCA6020)/Implementation/Python/Data"
ExogenousPath = "C:/Users/WilcoxJo/OneDrive - DVLA/Desktop/Independent Project (ACCA6020)/Implementation/Python/Predictors/Predictors.xlsx"
Future_Regresors = "C:/Users/WilcoxJo/OneDrive - DVLA/Desktop/Independent Project (ACCA6020)/Implementation/Python/Predictors/Future_Regresors.xlsx"
# Output file path
Output_path = "C:/Users/WilcoxJo/OneDrive - DVLA/Desktop/Independent Project (ACCA6020)/Implementation/Python/Outputs/"
# End Point in Data
EndMonth = pd.to_datetime("01/01/2026")
# Start Point in Data
StartMonth = pd.to_datetime("04/01/2018")
# Define transsaction to be used
transaction_service = "I Want To Tax My Vehicle"
# Transactions To Test
# I Want A Provisional Driving Licence (Done)
# I Want To Renew My Driving Licence (Done)
# I Want To Register A Vehicle (Done)
# I Want To Tax My Vehicle (Done)
# Forcast Periods
forcast_periods = 12
# Testing Period
testing_Periods = 12
# Run Models
# Setting to false will skip model
HoltWinters = False # Takes 1 Minute
Arima = True # Takes 4 Mins
prophet_Model = True # Takes 3 Mins
XGBOOST_Model = True # Takes 3 Seconds
Data Preperation¶
In [4]:
# ----------------------------------------
# Read Data In
# ----------------------------------------
# Read all Excel files in the specified folder, skipping the first 6 rows
all_files = glob.glob(path + "/*.xlsx")
dataframes = []
for filename in all_files:
df = pd.read_excel(filename, index_col=None, skiprows=6)
dataframes.append(df)
# Concatenate all data into a single dataframe
df = pd.concat(dataframes, axis=0, ignore_index=True)
# ----------------------------------------
# Clean & Filter Data
# ----------------------------------------
# Remove rows containing NULL values
df.dropna(inplace=True)
# Filter down to the specified transaction service to service set in config
df = df[df['Transaction Service'] == transaction_service]
# Convert 'Date' column to datetime format
df['Date'] = pd.to_datetime(df['Date'])
# Group by the start of each month and sum the 'Total' column
df = pd.DataFrame(df.groupby(pd.Grouper(key='Date', freq='MS'))['Total'].sum()).reset_index()
# Filter date to match data set in config
df = df[(df['Date'] >= StartMonth) & (df['Date'] <= EndMonth)]
# ----------------------------------------
# Exogenous Variables
# ----------------------------------------
# Exogenous variables are external factors that can influence the predicts - for example bank holidays.
# Load in exogenous variables
dataset_Predictors = pd.read_excel(ExogenousPath, sheet_name="Monthly")
# Select Columns
dataset_Predictors = dataset_Predictors[["Date", "Bank_Holidays_Count"]]
#Merge on exogenous variables by Date col
df = pd.merge( df, dataset_Predictors, on=["Date", "Date"])
# ----------------------------------------
# Other
# ----------------------------------------
# Rename the dependent variable columns
df = df.rename(columns={'Date': 'ds', 'Total': 'y'})
# Define empty variables to store RMSE scores from different forecasting models.
HW_RMSE_Score = None
Arima_Score = None
Prophet_RMSE_Result = None
XGboost_RMSE_Result = None
#Define empty list to store model results
all_results = []
future_predictions = []
model_metrics = []
In [5]:
# ----------------------------------------
# Store test data being used in a dataframe
# ----------------------------------------
# Split test data from data frame
test = df[-testing_Periods:]
model_output = pd.DataFrame({
"Date": test.ds,
"Transaction Service": transaction_service,
"total": test.y,
"Model": "Test Data"
})
all_results.append(model_output)
Explore The Data¶
In [6]:
# ----------------------------------------
# Set up dataframe to explore data
# ----------------------------------------
# Create a copy of the main input dataframe
df_Explore = df.copy()
# ----------------------------------------
# Create a plot displaying all data
# ----------------------------------------
# Plot directly using 'ds' as the x-axis
df_Explore.plot(x='ds', y='y', title=transaction_service, ylabel='Transactions', xlabel='Date', grid=True, legend=True)
# Display the plot
plt.show()
# ----------------------------------------
# Identify monthly trends
# ----------------------------------------
# Set 'ds' as the index
df_Explore.set_index('ds', inplace=True)
# Resample to monthly frequency and plot the mean
month_plot(df_Explore['y'].resample('M').mean(), ylabel='Demand')
# Display the plot
plt.show()
# ----------------------------------------
# Identify quarterly trends
# ----------------------------------------
# Resample to quarterly frequency and plot the mean
quarter_plot(df_Explore['y'].resample('Q').mean(), ylabel='Demand')
# Display the plot
plt.show()
# ----------------------------------------
# Seasonal Decomposition Plots
# ----------------------------------------
# This separates the time series into its seasonal, trend, and residual.
# The period is set to 12, assuming Monthly data.
# Apply seasonal decomposition to the 'y' column, using a multiplicative model and a yearly seasonality (12 months).
decomposition = seasonal_decompose(df_Explore['y'],
model='mul',
period=12)
# Plot the decomposition components (trend, seasonal, residual)
fig = decomposition.plot()
# Add a title
plt.suptitle('Seasonal Decomposition Chart', fontsize=16)
# Set the size of the plot
# Display
plt.show()
# ----------------------------------------
# Data Outliers
# ----------------------------------------
# Display histogram to identify any outliers
df_Explore['y'].plot(kind='hist', bins=20)
C:\Users\WilcoxJo\AppData\Local\Temp\ipykernel_43916\2697888512.py:26: FutureWarning: 'M' is deprecated and will be removed in a future version, please use 'ME' instead.
month_plot(df_Explore['y'].resample('M').mean(), ylabel='Demand')
C:\Users\WilcoxJo\AppData\Local\Temp\ipykernel_43916\2697888512.py:36: FutureWarning: 'Q' is deprecated and will be removed in a future version, please use 'QE' instead.
quarter_plot(df_Explore['y'].resample('Q').mean(), ylabel='Demand')
Out[6]:
<Axes: ylabel='Frequency'>
Holt-Winters Forecasting Model¶
Model not used in experement, very basic model used for quiick testing
In [7]:
# ----------------------------------------
# Holt-Winters Forecasting Model
# ----------------------------------------
#
if HoltWinters== True: # Only run section if set to true in config
# ----------------------------------------
# Set up dataframe
# ----------------------------------------
# Copy the dataframe
df_HW = df.copy()
#Set date to index field
df_HW.set_index('ds', inplace=True)
# ----------------------------------------
# Training and Test Split
# ----------------------------------------
# Select all rows except the last 'testing_Periods' rows for the training dataset
train = df_HW.iloc[:-testing_Periods, :]
# Select the last 'testing_Periods' rows for the test dataset
test = df_HW.iloc[-testing_Periods:, :]
# ----------------------------------------
# Hyper parameter tuning / Grid Search
# ----------------------------------------
# Defining the parameters to use
param_grid = {
'trend_mode': ['multiplicative', 'additive'],
'seasonality_mode': ['multiplicative', 'additive']
}
# Creating a ParameterGrid from the param_grid dictionary
# The ParameterGrid will generate all combinations of 'trend_mode' and 'seasonality_mode'
# This will result in a grid of parameter combinations for model tuning or evaluation
grid = ParameterGrid(param_grid)
# Initialize an empty list to store RMSE values
rmse = []
# Loop over each combination of parameters in the grid
for params in grid:
# Build model
model = ExponentialSmoothing(
endog=train.y, # 'Use Training dataset
trend=params['trend_mode'], # 'multiplicative' or 'additive'
seasonal=params['seasonality_mode'], # 'multiplicative' or 'additive'
seasonal_periods=12 # Number of periods in a season
).fit() # Fit the model to the training data
# Create predictions based on the trained model for the test data
predictions = model.forecast(steps=forcast_periods)
predictions = predictions.rename("HW")
# Use function to Evaluate the model's performance using RMSE (Root Mean Squared Error)
error = np.sqrt(mean_squared_error(test['y'], predictions))
# Append to list
rmse.append(error)
# Find the best parameter combination base on minimum RMSE
best_params = grid[np.argmin(rmse)]
# Output the best parameter combination
best_params
# ----------------------------------------
# Assess Model & Plot
# ----------------------------------------
# Plot chart test, vs train
plot_chart(train=train, test=test, predictions=predictions, title="Test vs Train")
# Calculate Mean Absolute Error (MAE)
mae = mean_absolute_error(test['y'], predictions)
rmse = mean_squared_error(test['y'], predictions, squared=False)
mape = mean_absolute_percentage_error(test['y'], predictions) * 100
# Print the calculated error metrics with proper formatting
print(f"The MAE is {mae:.2f}")
print(f"The RMSE is {rmse:.2f}")
print(f"The MAPE is {mape:.2f} %")
#Store evaluation metrics
HW_RMSE_Score = rmse
model_metrics.append({
"Model": "Holt-Winters",
"MAE": mae,
"RMSE": rmse,
"MAPE (%)": mape
})
# ----------------------------------------
# Predicting using the best parameters
# ----------------------------------------
# Fit the Exponential Smoothing model on the entire dataset using optimal parameters
model = ExponentialSmoothing(
endog=df_HW.y, # Dependent variable (time series data)
trend=best_params['trend_mode'], # Use best trend mode identified in best params
seasonal=best_params['seasonality_mode'], # Use best seasonality mode identified in best params
seasonal_periods=12 # 12 months for yearly seasonality
).fit()
# Generate forecasts for the specified number of future periods
predictions_hw = model.forecast(steps=forcast_periods).rename("HW")
# ----------------------------------------
# Plot predictions
# ----------------------------------------
plot_chart(data=df_HW, predictions = predictions_hw, title="Forecast")
# ----------------------------------------------------------------
# Save Future Predictions
# ----------------------------------------------------------------
futture_model_output = pd.DataFrame({
"Date": predictions_hw.index,
"Transaction Service": transaction_service,
"total": predictions_hw.values.flatten(),
"Model": "HW"
})
future_predictions.append(futture_model_output)
# ----------------------------------------
# Save Test Predictions
# ----------------------------------------
model_output = pd.DataFrame({
"Date": test.index,
"Transaction Service": transaction_service,
"total": predictions,
"Model": "HW"
})
all_results.append(model_output)
ARIMA Model¶
In [8]:
# ----------------------------------------
# ARIMA MODEL
# ----------------------------------------
if Arima == True: # Only run section if set to true in config
# Make a copy of the dataframe
df_ARIMA = df.copy()
#Set date to index field
df_ARIMA.set_index('ds', inplace=True)
#Set Date Frequence To MS (Monthly Start)
df_ARIMA.index.freq = 'MS'
# ----------------------------------------
# Training and Test Split
# ----------------------------------------
train = df_ARIMA.iloc[:-testing_Periods, :]
test = df_ARIMA.iloc[-testing_Periods:, :]
# Split the Regressor Data into training and test
# Regressors are external predictor variable
exog_train = df_ARIMA.iloc[:-testing_Periods,1:3]
exog_test = df_ARIMA.iloc[-testing_Periods:,1:3]
# ----------------------------------------
# Defining the parameter grid for model
# ----------------------------------------
# Defining the parameter grid for model
param_grid = {
'p': [1, 2, 3], # AR (Auto-Regressive) order
'd': [0, 1], # Differencing order (to make the series stationary)
'q': [1, 2, 3], # MA (Moving Average) order
'P': [1, 2], # Seasonal AR order
'D': [0], # Seasonal differencing order
'Q': [1, 2] # Seasonal MA order
}
# Generating all possible combinations of the parameters
grid = ParameterGrid(param_grid)
# Calculating the total number of parameter combinations
total_combinations = len(list(grid))
# Output the total number of combinations
print(f"Total number of parameter combinations: {total_combinations}")
# ----------------------------------------
# Build Model with parameter cobinations
# ----------------------------------------
# Initialize an empty list to store RMSE values for each parameter set
rmse_list = []
# Loop through each set of parameters generated from the grid
for params in grid:
# Build the ARIMA model with the current set of parameters
model = ARIMA(
order=(params['p'], params['d'], params['q']), # ARIMA (p, d, q)
seasonal_order=(params['P'], params['D'], params['Q'], 12) # Seasonal (P, D, Q, s), where s=12 (monthly seasonality)
)
# Define the Rolling Forecast Cross-Validation strategy
cv = model_selection.RollingForecastCV(
h=12, # Forecast horizon: number of steps ahead to predict
step=6, # Step size: how often the training window is moved forward
initial=None # Initial training window size; if None, defaults to 1/3 of time series length
)
# Perform cross-validation scoring with the ARIMA model
cv_score = model_selection.cross_val_score(
model,
y=train['y'], # Target variable
X=exog_train, # Exogenous variables
scoring='mean_squared_error', # Evaluation metric: Mean Squared Error (MSE)
cv=cv, # Cross-validation strategy
verbose=1,
error_score=10000000 # Assign a large error if model fitting fails
)
# Calculate RMSE (Root Mean Squared Error) from the cross-validation scores
rmse = np.sqrt(np.average(cv_score))
# Store the computed RMSE for the current parameter set
rmse_list.append(rmse)
# ----------------------------------------
# Display combinations & save best params
# ----------------------------------------
# Create a DataFrame to store the tuning parameters
tuning_results = pd.DataFrame(grid)
# Add the RMSE values calculated during parameter tuning to the DataFrame
tuning_results['rmse'] = rmse_list
# Display the tuning results DataFrame
print(tuning_results)
# Save the best parameters based on the minimum RMSE
best_params = tuning_results[tuning_results['rmse'] == tuning_results['rmse'].min()].transpose()
# Display the best parameters
print(best_params)
# ----------------------------------------
# Set up best parameters
# ----------------------------------------
# target variable
y = df_ARIMA['y']
# exogenous variables
X = df_ARIMA.iloc[:,1:3]
# Fetch the best parameters
p = int(best_params.loc['p'])
d = int(best_params.loc['d'])
q = int(best_params.loc['q'])
P = int(best_params.loc['P'])
D = int(best_params.loc['D'])
Q = int(best_params.loc['Q'])
# ----------------------------------------
# Use best parameters against test dataset
# ----------------------------------------
# Tuned ARIMA Model with the best parameters
tuned_model = ARIMA(order=(p, d, q),
seasonal_order=(P, D, Q, 12))
# Fit the model
tuned_model.fit(train['y'])
# Forecasting the next 12 periods
predictions = tuned_model.predict(n_periods=12)
# ----------------------------------------
# Assess Model & Plot
# ----------------------------------------
# Plot chart test, vs train
plot_chart(train=train, test=test, predictions=predictions)
# Calculating the MAE, RMSE, and MAPE for the forecast
mae = mean_absolute_error(test['y'], predictions)
rmse = mean_squared_error(test['y'], predictions, squared=False)
mape = mean_absolute_percentage_error(test['y'], predictions) * 100
# Print the calculated error metrics
print(f"The MAE is {mae:.2f}")
print(f"The RMSE is {rmse:.2f}")
print(f"The MAPE is {mape:.2f} %")
# Store evaluation metrics
Arima_Score = rmse
model_metrics.append({
"Model": "ARIMA",
"MAE": mae,
"RMSE": rmse,
"MAPE (%)": mape
})
# ----------------------------------------
# Set up future regressors for predictions
# ----------------------------------------
# Load the future regressors data from an Excel file
df_future = pd.read_excel(Future_Regresors)
# Set the 'Date' column as the DataFrame index for time series
df_future.set_index('Date', inplace=True)
# Set the frequency of the Date index to 'MS' (Month Start) for monthly data
df_future.index.freq = 'MS'
# Select specific regressor columns
X_future = df_future.iloc[:, 1:]
# ----------------------------------------
# Predict future
# ----------------------------------------
# Use Tuned Model with the best parameters
tuned_model = ARIMA(order = (p, d, q),
seasonal_order = (P, D, Q, 12))
# fit the model, add exogenous variables as X
tuned_model.fit(y, X = X)
# Forecasting
# set the number of periods to forecast # add future exogenous variables as X
predictions_ARIMA = tuned_model.predict(n_periods = len(X_future),
X = X_future)
# Plot chart predictions
plot_chart(data=df_ARIMA, predictions=predictions_ARIMA, title="Predictions")
# ----------------------------------------------------------------
# Save Future Predictions
# ----------------------------------------------------------------
futture_model_output = pd.DataFrame({
"Date": predictions_ARIMA.index,
"Transaction Service": transaction_service,
"total": predictions_ARIMA.values.flatten(),
"Model": "ARIMA"
})
future_predictions.append(futture_model_output)
# ----------------------------------------
# Save Test Predictions
# ----------------------------------------
model_output = pd.DataFrame({
"Date": test.index,
"Transaction Service": transaction_service,
"total": predictions,
"Model": "ARIMA"
})
all_results.append(model_output)
Total number of parameter combinations: 72
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:978: UserWarning: Non-invertible starting MA parameters found. Using zeros as starting parameters.
warn('Non-invertible starting MA parameters found.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:978: UserWarning: Non-invertible starting MA parameters found. Using zeros as starting parameters.
warn('Non-invertible starting MA parameters found.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:997: UserWarning: Non-stationary starting seasonal autoregressive Using zeros as starting parameters.
warn('Non-stationary starting seasonal autoregressive'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:997: UserWarning: Non-stationary starting seasonal autoregressive Using zeros as starting parameters.
warn('Non-stationary starting seasonal autoregressive'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:1009: UserWarning: Non-invertible starting seasonal moving average Using zeros as starting parameters.
warn('Non-invertible starting seasonal moving average'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:997: UserWarning: Non-stationary starting seasonal autoregressive Using zeros as starting parameters.
warn('Non-stationary starting seasonal autoregressive'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:997: UserWarning: Non-stationary starting seasonal autoregressive Using zeros as starting parameters.
warn('Non-stationary starting seasonal autoregressive'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:1009: UserWarning: Non-invertible starting seasonal moving average Using zeros as starting parameters.
warn('Non-invertible starting seasonal moving average'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:997: UserWarning: Non-stationary starting seasonal autoregressive Using zeros as starting parameters.
warn('Non-stationary starting seasonal autoregressive'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:997: UserWarning: Non-stationary starting seasonal autoregressive Using zeros as starting parameters.
warn('Non-stationary starting seasonal autoregressive'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:1009: UserWarning: Non-invertible starting seasonal moving average Using zeros as starting parameters.
warn('Non-invertible starting seasonal moving average'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:997: UserWarning: Non-stationary starting seasonal autoregressive Using zeros as starting parameters.
warn('Non-stationary starting seasonal autoregressive'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:997: UserWarning: Non-stationary starting seasonal autoregressive Using zeros as starting parameters.
warn('Non-stationary starting seasonal autoregressive'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:1009: UserWarning: Non-invertible starting seasonal moving average Using zeros as starting parameters.
warn('Non-invertible starting seasonal moving average'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:966: UserWarning: Non-stationary starting autoregressive parameters found. Using zeros as starting parameters.
warn('Non-stationary starting autoregressive parameters'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:966: UserWarning: Non-stationary starting autoregressive parameters found. Using zeros as starting parameters.
warn('Non-stationary starting autoregressive parameters'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:997: UserWarning: Non-stationary starting seasonal autoregressive Using zeros as starting parameters.
warn('Non-stationary starting seasonal autoregressive'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:997: UserWarning: Non-stationary starting seasonal autoregressive Using zeros as starting parameters.
warn('Non-stationary starting seasonal autoregressive'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:1009: UserWarning: Non-invertible starting seasonal moving average Using zeros as starting parameters.
warn('Non-invertible starting seasonal moving average'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:997: UserWarning: Non-stationary starting seasonal autoregressive Using zeros as starting parameters.
warn('Non-stationary starting seasonal autoregressive'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:997: UserWarning: Non-stationary starting seasonal autoregressive Using zeros as starting parameters.
warn('Non-stationary starting seasonal autoregressive'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:1009: UserWarning: Non-invertible starting seasonal moving average Using zeros as starting parameters.
warn('Non-invertible starting seasonal moving average'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:997: UserWarning: Non-stationary starting seasonal autoregressive Using zeros as starting parameters.
warn('Non-stationary starting seasonal autoregressive'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:997: UserWarning: Non-stationary starting seasonal autoregressive Using zeros as starting parameters.
warn('Non-stationary starting seasonal autoregressive'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:1009: UserWarning: Non-invertible starting seasonal moving average Using zeros as starting parameters.
warn('Non-invertible starting seasonal moving average'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:966: UserWarning: Non-stationary starting autoregressive parameters found. Using zeros as starting parameters.
warn('Non-stationary starting autoregressive parameters'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:997: UserWarning: Non-stationary starting seasonal autoregressive Using zeros as starting parameters.
warn('Non-stationary starting seasonal autoregressive'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:997: UserWarning: Non-stationary starting seasonal autoregressive Using zeros as starting parameters.
warn('Non-stationary starting seasonal autoregressive'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:1009: UserWarning: Non-invertible starting seasonal moving average Using zeros as starting parameters.
warn('Non-invertible starting seasonal moving average'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:997: UserWarning: Non-stationary starting seasonal autoregressive Using zeros as starting parameters.
warn('Non-stationary starting seasonal autoregressive'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:997: UserWarning: Non-stationary starting seasonal autoregressive Using zeros as starting parameters.
warn('Non-stationary starting seasonal autoregressive'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:1009: UserWarning: Non-invertible starting seasonal moving average Using zeros as starting parameters.
warn('Non-invertible starting seasonal moving average'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:966: UserWarning: Non-stationary starting autoregressive parameters found. Using zeros as starting parameters.
warn('Non-stationary starting autoregressive parameters'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:978: UserWarning: Non-invertible starting MA parameters found. Using zeros as starting parameters.
warn('Non-invertible starting MA parameters found.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:1009: UserWarning: Non-invertible starting seasonal moving average Using zeros as starting parameters.
warn('Non-invertible starting seasonal moving average'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:1009: UserWarning: Non-invertible starting seasonal moving average Using zeros as starting parameters.
warn('Non-invertible starting seasonal moving average'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:978: UserWarning: Non-invertible starting MA parameters found. Using zeros as starting parameters.
warn('Non-invertible starting MA parameters found.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:978: UserWarning: Non-invertible starting MA parameters found. Using zeros as starting parameters.
warn('Non-invertible starting MA parameters found.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:1009: UserWarning: Non-invertible starting seasonal moving average Using zeros as starting parameters.
warn('Non-invertible starting seasonal moving average'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:1009: UserWarning: Non-invertible starting seasonal moving average Using zeros as starting parameters.
warn('Non-invertible starting seasonal moving average'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:978: UserWarning: Non-invertible starting MA parameters found. Using zeros as starting parameters.
warn('Non-invertible starting MA parameters found.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:1009: UserWarning: Non-invertible starting seasonal moving average Using zeros as starting parameters.
warn('Non-invertible starting seasonal moving average'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:1009: UserWarning: Non-invertible starting seasonal moving average Using zeros as starting parameters.
warn('Non-invertible starting seasonal moving average'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:966: UserWarning: Non-stationary starting autoregressive parameters found. Using zeros as starting parameters.
warn('Non-stationary starting autoregressive parameters'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:978: UserWarning: Non-invertible starting MA parameters found. Using zeros as starting parameters.
warn('Non-invertible starting MA parameters found.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:1009: UserWarning: Non-invertible starting seasonal moving average Using zeros as starting parameters.
warn('Non-invertible starting seasonal moving average'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:1009: UserWarning: Non-invertible starting seasonal moving average Using zeros as starting parameters.
warn('Non-invertible starting seasonal moving average'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:978: UserWarning: Non-invertible starting MA parameters found. Using zeros as starting parameters.
warn('Non-invertible starting MA parameters found.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:1009: UserWarning: Non-invertible starting seasonal moving average Using zeros as starting parameters.
warn('Non-invertible starting seasonal moving average'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:1009: UserWarning: Non-invertible starting seasonal moving average Using zeros as starting parameters.
warn('Non-invertible starting seasonal moving average'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:966: UserWarning: Non-stationary starting autoregressive parameters found. Using zeros as starting parameters.
warn('Non-stationary starting autoregressive parameters'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:1009: UserWarning: Non-invertible starting seasonal moving average Using zeros as starting parameters.
warn('Non-invertible starting seasonal moving average'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:1009: UserWarning: Non-invertible starting seasonal moving average Using zeros as starting parameters.
warn('Non-invertible starting seasonal moving average'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:1009: UserWarning: Non-invertible starting seasonal moving average Using zeros as starting parameters.
warn('Non-invertible starting seasonal moving average'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:1009: UserWarning: Non-invertible starting seasonal moving average Using zeros as starting parameters.
warn('Non-invertible starting seasonal moving average'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:978: UserWarning: Non-invertible starting MA parameters found. Using zeros as starting parameters.
warn('Non-invertible starting MA parameters found.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:978: UserWarning: Non-invertible starting MA parameters found. Using zeros as starting parameters.
warn('Non-invertible starting MA parameters found.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:966: UserWarning: Non-stationary starting autoregressive parameters found. Using zeros as starting parameters.
warn('Non-stationary starting autoregressive parameters'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:978: UserWarning: Non-invertible starting MA parameters found. Using zeros as starting parameters.
warn('Non-invertible starting MA parameters found.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:1009: UserWarning: Non-invertible starting seasonal moving average Using zeros as starting parameters.
warn('Non-invertible starting seasonal moving average'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:966: UserWarning: Non-stationary starting autoregressive parameters found. Using zeros as starting parameters.
warn('Non-stationary starting autoregressive parameters'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:978: UserWarning: Non-invertible starting MA parameters found. Using zeros as starting parameters.
warn('Non-invertible starting MA parameters found.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:966: UserWarning: Non-stationary starting autoregressive parameters found. Using zeros as starting parameters.
warn('Non-stationary starting autoregressive parameters'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:978: UserWarning: Non-invertible starting MA parameters found. Using zeros as starting parameters.
warn('Non-invertible starting MA parameters found.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:1009: UserWarning: Non-invertible starting seasonal moving average Using zeros as starting parameters.
warn('Non-invertible starting seasonal moving average'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:966: UserWarning: Non-stationary starting autoregressive parameters found. Using zeros as starting parameters.
warn('Non-stationary starting autoregressive parameters'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:978: UserWarning: Non-invertible starting MA parameters found. Using zeros as starting parameters.
warn('Non-invertible starting MA parameters found.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:966: UserWarning: Non-stationary starting autoregressive parameters found. Using zeros as starting parameters.
warn('Non-stationary starting autoregressive parameters'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:978: UserWarning: Non-invertible starting MA parameters found. Using zeros as starting parameters.
warn('Non-invertible starting MA parameters found.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:966: UserWarning: Non-stationary starting autoregressive parameters found. Using zeros as starting parameters.
warn('Non-stationary starting autoregressive parameters'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:978: UserWarning: Non-invertible starting MA parameters found. Using zeros as starting parameters.
warn('Non-invertible starting MA parameters found.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:1009: UserWarning: Non-invertible starting seasonal moving average Using zeros as starting parameters.
warn('Non-invertible starting seasonal moving average'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:1009: UserWarning: Non-invertible starting seasonal moving average Using zeros as starting parameters.
warn('Non-invertible starting seasonal moving average'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:966: UserWarning: Non-stationary starting autoregressive parameters found. Using zeros as starting parameters.
warn('Non-stationary starting autoregressive parameters'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:978: UserWarning: Non-invertible starting MA parameters found. Using zeros as starting parameters.
warn('Non-invertible starting MA parameters found.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:978: UserWarning: Non-invertible starting MA parameters found. Using zeros as starting parameters.
warn('Non-invertible starting MA parameters found.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:978: UserWarning: Non-invertible starting MA parameters found. Using zeros as starting parameters.
warn('Non-invertible starting MA parameters found.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:966: UserWarning: Non-stationary starting autoregressive parameters found. Using zeros as starting parameters.
warn('Non-stationary starting autoregressive parameters'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:966: UserWarning: Non-stationary starting autoregressive parameters found. Using zeros as starting parameters.
warn('Non-stationary starting autoregressive parameters'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:966: UserWarning: Non-stationary starting autoregressive parameters found. Using zeros as starting parameters.
warn('Non-stationary starting autoregressive parameters'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:966: UserWarning: Non-stationary starting autoregressive parameters found. Using zeros as starting parameters.
warn('Non-stationary starting autoregressive parameters'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:978: UserWarning: Non-invertible starting MA parameters found. Using zeros as starting parameters.
warn('Non-invertible starting MA parameters found.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:978: UserWarning: Non-invertible starting MA parameters found. Using zeros as starting parameters.
warn('Non-invertible starting MA parameters found.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:978: UserWarning: Non-invertible starting MA parameters found. Using zeros as starting parameters.
warn('Non-invertible starting MA parameters found.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:978: UserWarning: Non-invertible starting MA parameters found. Using zeros as starting parameters.
warn('Non-invertible starting MA parameters found.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:966: UserWarning: Non-stationary starting autoregressive parameters found. Using zeros as starting parameters.
warn('Non-stationary starting autoregressive parameters'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:978: UserWarning: Non-invertible starting MA parameters found. Using zeros as starting parameters.
warn('Non-invertible starting MA parameters found.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:978: UserWarning: Non-invertible starting MA parameters found. Using zeros as starting parameters.
warn('Non-invertible starting MA parameters found.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:966: UserWarning: Non-stationary starting autoregressive parameters found. Using zeros as starting parameters.
warn('Non-stationary starting autoregressive parameters'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:978: UserWarning: Non-invertible starting MA parameters found. Using zeros as starting parameters.
warn('Non-invertible starting MA parameters found.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:978: UserWarning: Non-invertible starting MA parameters found. Using zeros as starting parameters.
warn('Non-invertible starting MA parameters found.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:966: UserWarning: Non-stationary starting autoregressive parameters found. Using zeros as starting parameters.
warn('Non-stationary starting autoregressive parameters'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:978: UserWarning: Non-invertible starting MA parameters found. Using zeros as starting parameters.
warn('Non-invertible starting MA parameters found.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:966: UserWarning: Non-stationary starting autoregressive parameters found. Using zeros as starting parameters.
warn('Non-stationary starting autoregressive parameters'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:978: UserWarning: Non-invertible starting MA parameters found. Using zeros as starting parameters.
warn('Non-invertible starting MA parameters found.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:966: UserWarning: Non-stationary starting autoregressive parameters found. Using zeros as starting parameters.
warn('Non-stationary starting autoregressive parameters'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:978: UserWarning: Non-invertible starting MA parameters found. Using zeros as starting parameters.
warn('Non-invertible starting MA parameters found.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:966: UserWarning: Non-stationary starting autoregressive parameters found. Using zeros as starting parameters.
warn('Non-stationary starting autoregressive parameters'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:978: UserWarning: Non-invertible starting MA parameters found. Using zeros as starting parameters.
warn('Non-invertible starting MA parameters found.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:966: UserWarning: Non-stationary starting autoregressive parameters found. Using zeros as starting parameters.
warn('Non-stationary starting autoregressive parameters'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:978: UserWarning: Non-invertible starting MA parameters found. Using zeros as starting parameters.
warn('Non-invertible starting MA parameters found.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:966: UserWarning: Non-stationary starting autoregressive parameters found. Using zeros as starting parameters.
warn('Non-stationary starting autoregressive parameters'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:978: UserWarning: Non-invertible starting MA parameters found. Using zeros as starting parameters.
warn('Non-invertible starting MA parameters found.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:966: UserWarning: Non-stationary starting autoregressive parameters found. Using zeros as starting parameters.
warn('Non-stationary starting autoregressive parameters'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:978: UserWarning: Non-invertible starting MA parameters found. Using zeros as starting parameters.
warn('Non-invertible starting MA parameters found.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:978: UserWarning: Non-invertible starting MA parameters found. Using zeros as starting parameters.
warn('Non-invertible starting MA parameters found.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:978: UserWarning: Non-invertible starting MA parameters found. Using zeros as starting parameters.
warn('Non-invertible starting MA parameters found.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:997: UserWarning: Non-stationary starting seasonal autoregressive Using zeros as starting parameters.
warn('Non-stationary starting seasonal autoregressive'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:997: UserWarning: Non-stationary starting seasonal autoregressive Using zeros as starting parameters.
warn('Non-stationary starting seasonal autoregressive'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:1009: UserWarning: Non-invertible starting seasonal moving average Using zeros as starting parameters.
warn('Non-invertible starting seasonal moving average'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:997: UserWarning: Non-stationary starting seasonal autoregressive Using zeros as starting parameters.
warn('Non-stationary starting seasonal autoregressive'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:997: UserWarning: Non-stationary starting seasonal autoregressive Using zeros as starting parameters.
warn('Non-stationary starting seasonal autoregressive'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:1009: UserWarning: Non-invertible starting seasonal moving average Using zeros as starting parameters.
warn('Non-invertible starting seasonal moving average'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:997: UserWarning: Non-stationary starting seasonal autoregressive Using zeros as starting parameters.
warn('Non-stationary starting seasonal autoregressive'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:997: UserWarning: Non-stationary starting seasonal autoregressive Using zeros as starting parameters.
warn('Non-stationary starting seasonal autoregressive'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:1009: UserWarning: Non-invertible starting seasonal moving average Using zeros as starting parameters.
warn('Non-invertible starting seasonal moving average'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:997: UserWarning: Non-stationary starting seasonal autoregressive Using zeros as starting parameters.
warn('Non-stationary starting seasonal autoregressive'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:997: UserWarning: Non-stationary starting seasonal autoregressive Using zeros as starting parameters.
warn('Non-stationary starting seasonal autoregressive'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:1009: UserWarning: Non-invertible starting seasonal moving average Using zeros as starting parameters.
warn('Non-invertible starting seasonal moving average'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:966: UserWarning: Non-stationary starting autoregressive parameters found. Using zeros as starting parameters.
warn('Non-stationary starting autoregressive parameters'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:966: UserWarning: Non-stationary starting autoregressive parameters found. Using zeros as starting parameters.
warn('Non-stationary starting autoregressive parameters'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:997: UserWarning: Non-stationary starting seasonal autoregressive Using zeros as starting parameters.
warn('Non-stationary starting seasonal autoregressive'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:997: UserWarning: Non-stationary starting seasonal autoregressive Using zeros as starting parameters.
warn('Non-stationary starting seasonal autoregressive'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:1009: UserWarning: Non-invertible starting seasonal moving average Using zeros as starting parameters.
warn('Non-invertible starting seasonal moving average'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:997: UserWarning: Non-stationary starting seasonal autoregressive Using zeros as starting parameters.
warn('Non-stationary starting seasonal autoregressive'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:997: UserWarning: Non-stationary starting seasonal autoregressive Using zeros as starting parameters.
warn('Non-stationary starting seasonal autoregressive'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:1009: UserWarning: Non-invertible starting seasonal moving average Using zeros as starting parameters.
warn('Non-invertible starting seasonal moving average'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:997: UserWarning: Non-stationary starting seasonal autoregressive Using zeros as starting parameters.
warn('Non-stationary starting seasonal autoregressive'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:997: UserWarning: Non-stationary starting seasonal autoregressive Using zeros as starting parameters.
warn('Non-stationary starting seasonal autoregressive'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:1009: UserWarning: Non-invertible starting seasonal moving average Using zeros as starting parameters.
warn('Non-invertible starting seasonal moving average'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:966: UserWarning: Non-stationary starting autoregressive parameters found. Using zeros as starting parameters.
warn('Non-stationary starting autoregressive parameters'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:997: UserWarning: Non-stationary starting seasonal autoregressive Using zeros as starting parameters.
warn('Non-stationary starting seasonal autoregressive'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:997: UserWarning: Non-stationary starting seasonal autoregressive Using zeros as starting parameters.
warn('Non-stationary starting seasonal autoregressive'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:1009: UserWarning: Non-invertible starting seasonal moving average Using zeros as starting parameters.
warn('Non-invertible starting seasonal moving average'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:997: UserWarning: Non-stationary starting seasonal autoregressive Using zeros as starting parameters.
warn('Non-stationary starting seasonal autoregressive'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:997: UserWarning: Non-stationary starting seasonal autoregressive Using zeros as starting parameters.
warn('Non-stationary starting seasonal autoregressive'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:1009: UserWarning: Non-invertible starting seasonal moving average Using zeros as starting parameters.
warn('Non-invertible starting seasonal moving average'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:966: UserWarning: Non-stationary starting autoregressive parameters found. Using zeros as starting parameters.
warn('Non-stationary starting autoregressive parameters'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:978: UserWarning: Non-invertible starting MA parameters found. Using zeros as starting parameters.
warn('Non-invertible starting MA parameters found.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:1009: UserWarning: Non-invertible starting seasonal moving average Using zeros as starting parameters.
warn('Non-invertible starting seasonal moving average'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:1009: UserWarning: Non-invertible starting seasonal moving average Using zeros as starting parameters.
warn('Non-invertible starting seasonal moving average'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:1009: UserWarning: Non-invertible starting seasonal moving average Using zeros as starting parameters.
warn('Non-invertible starting seasonal moving average'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:978: UserWarning: Non-invertible starting MA parameters found. Using zeros as starting parameters.
warn('Non-invertible starting MA parameters found.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:978: UserWarning: Non-invertible starting MA parameters found. Using zeros as starting parameters.
warn('Non-invertible starting MA parameters found.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:1009: UserWarning: Non-invertible starting seasonal moving average Using zeros as starting parameters.
warn('Non-invertible starting seasonal moving average'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:1009: UserWarning: Non-invertible starting seasonal moving average Using zeros as starting parameters.
warn('Non-invertible starting seasonal moving average'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:1009: UserWarning: Non-invertible starting seasonal moving average Using zeros as starting parameters.
warn('Non-invertible starting seasonal moving average'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:978: UserWarning: Non-invertible starting MA parameters found. Using zeros as starting parameters.
warn('Non-invertible starting MA parameters found.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:1009: UserWarning: Non-invertible starting seasonal moving average Using zeros as starting parameters.
warn('Non-invertible starting seasonal moving average'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:1009: UserWarning: Non-invertible starting seasonal moving average Using zeros as starting parameters.
warn('Non-invertible starting seasonal moving average'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:1009: UserWarning: Non-invertible starting seasonal moving average Using zeros as starting parameters.
warn('Non-invertible starting seasonal moving average'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:966: UserWarning: Non-stationary starting autoregressive parameters found. Using zeros as starting parameters.
warn('Non-stationary starting autoregressive parameters'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:978: UserWarning: Non-invertible starting MA parameters found. Using zeros as starting parameters.
warn('Non-invertible starting MA parameters found.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:1009: UserWarning: Non-invertible starting seasonal moving average Using zeros as starting parameters.
warn('Non-invertible starting seasonal moving average'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:1009: UserWarning: Non-invertible starting seasonal moving average Using zeros as starting parameters.
warn('Non-invertible starting seasonal moving average'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:1009: UserWarning: Non-invertible starting seasonal moving average Using zeros as starting parameters.
warn('Non-invertible starting seasonal moving average'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:978: UserWarning: Non-invertible starting MA parameters found. Using zeros as starting parameters.
warn('Non-invertible starting MA parameters found.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:1009: UserWarning: Non-invertible starting seasonal moving average Using zeros as starting parameters.
warn('Non-invertible starting seasonal moving average'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:1009: UserWarning: Non-invertible starting seasonal moving average Using zeros as starting parameters.
warn('Non-invertible starting seasonal moving average'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:1009: UserWarning: Non-invertible starting seasonal moving average Using zeros as starting parameters.
warn('Non-invertible starting seasonal moving average'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:966: UserWarning: Non-stationary starting autoregressive parameters found. Using zeros as starting parameters.
warn('Non-stationary starting autoregressive parameters'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:1009: UserWarning: Non-invertible starting seasonal moving average Using zeros as starting parameters.
warn('Non-invertible starting seasonal moving average'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:1009: UserWarning: Non-invertible starting seasonal moving average Using zeros as starting parameters.
warn('Non-invertible starting seasonal moving average'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:1009: UserWarning: Non-invertible starting seasonal moving average Using zeros as starting parameters.
warn('Non-invertible starting seasonal moving average'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:1009: UserWarning: Non-invertible starting seasonal moving average Using zeros as starting parameters.
warn('Non-invertible starting seasonal moving average'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:1009: UserWarning: Non-invertible starting seasonal moving average Using zeros as starting parameters.
warn('Non-invertible starting seasonal moving average'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:1009: UserWarning: Non-invertible starting seasonal moving average Using zeros as starting parameters.
warn('Non-invertible starting seasonal moving average'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:978: UserWarning: Non-invertible starting MA parameters found. Using zeros as starting parameters.
warn('Non-invertible starting MA parameters found.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:978: UserWarning: Non-invertible starting MA parameters found. Using zeros as starting parameters.
warn('Non-invertible starting MA parameters found.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:966: UserWarning: Non-stationary starting autoregressive parameters found. Using zeros as starting parameters.
warn('Non-stationary starting autoregressive parameters'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:978: UserWarning: Non-invertible starting MA parameters found. Using zeros as starting parameters.
warn('Non-invertible starting MA parameters found.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:1009: UserWarning: Non-invertible starting seasonal moving average Using zeros as starting parameters.
warn('Non-invertible starting seasonal moving average'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:966: UserWarning: Non-stationary starting autoregressive parameters found. Using zeros as starting parameters.
warn('Non-stationary starting autoregressive parameters'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:978: UserWarning: Non-invertible starting MA parameters found. Using zeros as starting parameters.
warn('Non-invertible starting MA parameters found.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:966: UserWarning: Non-stationary starting autoregressive parameters found. Using zeros as starting parameters.
warn('Non-stationary starting autoregressive parameters'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:978: UserWarning: Non-invertible starting MA parameters found. Using zeros as starting parameters.
warn('Non-invertible starting MA parameters found.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:1009: UserWarning: Non-invertible starting seasonal moving average Using zeros as starting parameters.
warn('Non-invertible starting seasonal moving average'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:966: UserWarning: Non-stationary starting autoregressive parameters found. Using zeros as starting parameters.
warn('Non-stationary starting autoregressive parameters'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:978: UserWarning: Non-invertible starting MA parameters found. Using zeros as starting parameters.
warn('Non-invertible starting MA parameters found.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:1009: UserWarning: Non-invertible starting seasonal moving average Using zeros as starting parameters.
warn('Non-invertible starting seasonal moving average'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:966: UserWarning: Non-stationary starting autoregressive parameters found. Using zeros as starting parameters.
warn('Non-stationary starting autoregressive parameters'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:978: UserWarning: Non-invertible starting MA parameters found. Using zeros as starting parameters.
warn('Non-invertible starting MA parameters found.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:966: UserWarning: Non-stationary starting autoregressive parameters found. Using zeros as starting parameters.
warn('Non-stationary starting autoregressive parameters'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:978: UserWarning: Non-invertible starting MA parameters found. Using zeros as starting parameters.
warn('Non-invertible starting MA parameters found.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:1009: UserWarning: Non-invertible starting seasonal moving average Using zeros as starting parameters.
warn('Non-invertible starting seasonal moving average'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:1009: UserWarning: Non-invertible starting seasonal moving average Using zeros as starting parameters.
warn('Non-invertible starting seasonal moving average'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:966: UserWarning: Non-stationary starting autoregressive parameters found. Using zeros as starting parameters.
warn('Non-stationary starting autoregressive parameters'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:978: UserWarning: Non-invertible starting MA parameters found. Using zeros as starting parameters.
warn('Non-invertible starting MA parameters found.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:1009: UserWarning: Non-invertible starting seasonal moving average Using zeros as starting parameters.
warn('Non-invertible starting seasonal moving average'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:978: UserWarning: Non-invertible starting MA parameters found. Using zeros as starting parameters.
warn('Non-invertible starting MA parameters found.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:978: UserWarning: Non-invertible starting MA parameters found. Using zeros as starting parameters.
warn('Non-invertible starting MA parameters found.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:966: UserWarning: Non-stationary starting autoregressive parameters found. Using zeros as starting parameters.
warn('Non-stationary starting autoregressive parameters'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:966: UserWarning: Non-stationary starting autoregressive parameters found. Using zeros as starting parameters.
warn('Non-stationary starting autoregressive parameters'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:966: UserWarning: Non-stationary starting autoregressive parameters found. Using zeros as starting parameters.
warn('Non-stationary starting autoregressive parameters'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:966: UserWarning: Non-stationary starting autoregressive parameters found. Using zeros as starting parameters.
warn('Non-stationary starting autoregressive parameters'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:978: UserWarning: Non-invertible starting MA parameters found. Using zeros as starting parameters.
warn('Non-invertible starting MA parameters found.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:978: UserWarning: Non-invertible starting MA parameters found. Using zeros as starting parameters.
warn('Non-invertible starting MA parameters found.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:978: UserWarning: Non-invertible starting MA parameters found. Using zeros as starting parameters.
warn('Non-invertible starting MA parameters found.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:978: UserWarning: Non-invertible starting MA parameters found. Using zeros as starting parameters.
warn('Non-invertible starting MA parameters found.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:966: UserWarning: Non-stationary starting autoregressive parameters found. Using zeros as starting parameters.
warn('Non-stationary starting autoregressive parameters'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:978: UserWarning: Non-invertible starting MA parameters found. Using zeros as starting parameters.
warn('Non-invertible starting MA parameters found.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:978: UserWarning: Non-invertible starting MA parameters found. Using zeros as starting parameters.
warn('Non-invertible starting MA parameters found.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:966: UserWarning: Non-stationary starting autoregressive parameters found. Using zeros as starting parameters.
warn('Non-stationary starting autoregressive parameters'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:978: UserWarning: Non-invertible starting MA parameters found. Using zeros as starting parameters.
warn('Non-invertible starting MA parameters found.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:978: UserWarning: Non-invertible starting MA parameters found. Using zeros as starting parameters.
warn('Non-invertible starting MA parameters found.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:966: UserWarning: Non-stationary starting autoregressive parameters found. Using zeros as starting parameters.
warn('Non-stationary starting autoregressive parameters'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:978: UserWarning: Non-invertible starting MA parameters found. Using zeros as starting parameters.
warn('Non-invertible starting MA parameters found.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:966: UserWarning: Non-stationary starting autoregressive parameters found. Using zeros as starting parameters.
warn('Non-stationary starting autoregressive parameters'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:978: UserWarning: Non-invertible starting MA parameters found. Using zeros as starting parameters.
warn('Non-invertible starting MA parameters found.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:966: UserWarning: Non-stationary starting autoregressive parameters found. Using zeros as starting parameters.
warn('Non-stationary starting autoregressive parameters'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:978: UserWarning: Non-invertible starting MA parameters found. Using zeros as starting parameters.
warn('Non-invertible starting MA parameters found.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:966: UserWarning: Non-stationary starting autoregressive parameters found. Using zeros as starting parameters.
warn('Non-stationary starting autoregressive parameters'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:978: UserWarning: Non-invertible starting MA parameters found. Using zeros as starting parameters.
warn('Non-invertible starting MA parameters found.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:966: UserWarning: Non-stationary starting autoregressive parameters found. Using zeros as starting parameters.
warn('Non-stationary starting autoregressive parameters'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:978: UserWarning: Non-invertible starting MA parameters found. Using zeros as starting parameters.
warn('Non-invertible starting MA parameters found.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:966: UserWarning: Non-stationary starting autoregressive parameters found. Using zeros as starting parameters.
warn('Non-stationary starting autoregressive parameters'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:978: UserWarning: Non-invertible starting MA parameters found. Using zeros as starting parameters.
warn('Non-invertible starting MA parameters found.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:966: UserWarning: Non-stationary starting autoregressive parameters found. Using zeros as starting parameters.
warn('Non-stationary starting autoregressive parameters'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:978: UserWarning: Non-invertible starting MA parameters found. Using zeros as starting parameters.
warn('Non-invertible starting MA parameters found.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\tsa\statespace\sarimax.py:866: UserWarning: Too few observations to estimate starting parameters for seasonal ARMA. All parameters except for variances will be set to zeros.
warn('Too few observations to estimate starting parameters%s.'
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\statsmodels\base\model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
D P Q d p q rmse
0 0 1 1 0 1 1 8.385982e+05
1 0 1 1 0 1 2 1.082176e+06
2 0 1 1 0 1 3 1.034462e+06
3 0 1 1 0 2 1 9.663742e+05
4 0 1 1 0 2 2 8.586815e+05
.. .. .. .. .. .. .. ...
67 0 2 2 1 2 2 6.313081e+05
68 0 2 2 1 2 3 8.045999e+05
69 0 2 2 1 3 1 7.367749e+05
70 0 2 2 1 3 2 6.567769e+05
71 0 2 2 1 3 3 6.912713e+05
[72 rows x 7 columns]
11
D 0.00000
P 1.00000
Q 1.00000
d 1.00000
p 1.00000
q 3.00000
rmse 505917.91984
C:\Users\WilcoxJo\AppData\Local\Temp\ipykernel_43916\1396318490.py:120: FutureWarning: Calling int on a single element Series is deprecated and will raise a TypeError in the future. Use int(ser.iloc[0]) instead p = int(best_params.loc['p']) C:\Users\WilcoxJo\AppData\Local\Temp\ipykernel_43916\1396318490.py:121: FutureWarning: Calling int on a single element Series is deprecated and will raise a TypeError in the future. Use int(ser.iloc[0]) instead d = int(best_params.loc['d']) C:\Users\WilcoxJo\AppData\Local\Temp\ipykernel_43916\1396318490.py:122: FutureWarning: Calling int on a single element Series is deprecated and will raise a TypeError in the future. Use int(ser.iloc[0]) instead q = int(best_params.loc['q']) C:\Users\WilcoxJo\AppData\Local\Temp\ipykernel_43916\1396318490.py:123: FutureWarning: Calling int on a single element Series is deprecated and will raise a TypeError in the future. Use int(ser.iloc[0]) instead P = int(best_params.loc['P']) C:\Users\WilcoxJo\AppData\Local\Temp\ipykernel_43916\1396318490.py:124: FutureWarning: Calling int on a single element Series is deprecated and will raise a TypeError in the future. Use int(ser.iloc[0]) instead D = int(best_params.loc['D']) C:\Users\WilcoxJo\AppData\Local\Temp\ipykernel_43916\1396318490.py:125: FutureWarning: Calling int on a single element Series is deprecated and will raise a TypeError in the future. Use int(ser.iloc[0]) instead Q = int(best_params.loc['Q'])
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\sklearn\metrics\_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn(
The MAE is 275652.88 The RMSE is 327019.88 The MAPE is 6.84 %
Prophet Model¶
In [9]:
# ----------------------------------------
# Prophet Model
# ----------------------------------------
if prophet_Model == True: # Only run section if set to true in config
# Copy the dataframe
df_Prophet = df.copy()
# ----------------------------------------
# Training and Test Split
# ----------------------------------------
Prophet_training_set = df.iloc[:-testing_Periods, :]
Prophet_test_set = df.iloc[-testing_Periods:, :]
# -------------------------------------------------
# define paramaeter grid for hyperparameter tuning
# -------------------------------------------------
# Define the grid of hyperparameters for tuning the Prophet model
param_grid = {
'changepoint_prior_scale': [0.05, 0.5], # Controls flexibility
'seasonality_prior_scale': [10, 20], # Controls strength of seasonality
# 'holidays_prior_scale': [10, 20], # Uncomment if holidays are included
'seasonality_mode': ['additive', 'multiplicative'] # Type of seasonality to apply
}
# Generate all possible combinations of the hyperparameters
all_params = list(ParameterGrid(param_grid))
# Display the parameter combinations
all_params
# ------------------------------------------------------------
# Hyperparameter Tuning - Model Training and Cross-Validation
# ------------------------------------------------------------
# Placeholder list to store RMSE results for each parameter combination
tuning_results = []
# Iterate over each set of parameters from the grid search
for params in all_params:
# Build the Prophet model with current hyperparameters
m = Prophet(
yearly_seasonality=True,
weekly_seasonality=True,
**params # Use hyperparameters from the grid
)
# Add external regressor to the model
m.add_regressor("Bank_Holidays_Count")
# Fit the model to the training dataset
m.fit(Prophet_training_set)
# Perform cross-validation
df_cv = cross_validation(
model=m,
horizon='365.25 days', # Forecast horizon (1 year)
initial='365.25 days', # Initial training period (1 year)
parallel="processes"
)
##Use prophet performance_metrics
performance_metrics(df_cv)
# Store the Error
rmse = performance_metrics(df_cv)['rmse'].mean()
tuning_results.append(rmse)
# ------------------------------------------
# Parameter Tuning Outcome - Results Summary
# ------------------------------------------
# Create a DataFrame to store all tested parameter combinations
outcome = pd.DataFrame(all_params)
# Add the corresponding RMSE results to the DataFrame
outcome['tuning_results'] = tuning_results
# Display the final tuning results
outcome
# --------------------------------------
# Get the Best Hyperparameters
# --------------------------------------
# Identify the index of the parameter set with the lowest RMSE (best performance)
best_index = tuning_results.index(min(tuning_results))
# Retrieve the best hyperparameter combination using the identified index
best_params = all_params[best_index]
# Print the best hyperparameters
print(best_params)
# --------------------------------------------------------
# Build the Final Prophet Model with Best Hyperparameters
# --------------------------------------------------------
# Initialize the Prophet model using the best-found hyperparameters
m = Prophet(
yearly_seasonality=True,
weekly_seasonality=True,
**best_params # Use the best hyperparameters from tuning
)
# Add the external regressor 'Bank_Holidays_Count' to the model
m.add_regressor("Bank_Holidays_Count")
# Fit the model on the full training dataset
m.fit(Prophet_training_set)
# ---------------------------------------------------
# Create Future DataFrame & Forecasting usin test set
# ---------------------------------------------------
# Generate future dates for forecasting, matching the length of the test set
future = m.make_future_dataframe(
periods=len(Prophet_test_set), # Number of future periods to predict
freq="MS"
)
# Concatenate the future dates with additional regressors
future = pd.concat(
[future, df_Prophet.iloc[:, 1:]],
axis=1
)
# Display the future DataFrame ready for prediction
future
#forecast future
forecast = m.predict(future)
forecast.head()
#visualization forecast
m.plot(forecast);
# ---------------------------------------------------
# Extract predictions for test
# ---------------------------------------------------
predictions_prophet_tuned = forecast.yhat[-testing_Periods:].rename("prophet_tuned")
predictions_prophet_tuned.index = Prophet_test_set["ds"]
predictions_prophet_tuned
# ----------------------------------------------
# Model Evaluation (Match other model versions)
# ----------------------------------------------
# Calculate Mean Absolute Error (MAE)
mae = mean_absolute_error(Prophet_test_set['y'], predictions_prophet_tuned)
# Calculate Root Mean Squared Error (RMSE)
rmse = mean_squared_error(Prophet_test_set['y'], predictions_prophet_tuned, squared=False)
# Calculate Mean Absolute Percentage Error (MAPE)
mape = mean_absolute_percentage_error(Prophet_test_set['y'], predictions_prophet_tuned) * 100
# Print evaluation metrics
print(f"The MAE is {mae:.2f}")
print(f"The RMSE is {rmse:.2f}")
print(f"The MAPE is {mape:.2f} %")
# Store RMSE score for model comparison
prophet_rmse = rmse
model_metrics.append({
"Model": "Prophet",
"MAE": mae,
"RMSE": rmse,
"MAPE (%)": mape
})
# Calculate RMSE using the new function
Prophet_RMSE_Result = root_mean_squared_error(Prophet_test_set['y'], predictions_prophet_tuned)
# ---------------------------------------------------
# Predict Future with best parameters
# ---------------------------------------------------
# Building the Prophet model
m = Prophet(
yearly_seasonality=True,
weekly_seasonality= True,
**best_params)
m.add_regressor("Bank_Holidays_Count")
m.fit(df_Prophet)
dataset_Predictors.rename(columns={'Date': 'ds'}, inplace=True)
dataset_Predictors
# Create a future dataframe using Prophet's make_future_dataframe
future = m.make_future_dataframe(periods = 12,
freq = "MS")
#Merge on exogenous variables
future = pd.merge( future, dataset_Predictors, on=["ds", "ds"])
#forecast
forecast = m.predict(future)
forecast
#visualization forecast
m.plot(forecast);
# ----------------------------------------------------------------
# Extract the last 12 predicted values from the Prophet forecast
# ----------------------------------------------------------------
# Rename the prediction series
prophet_predictions = forecast.yhat[-12:].rename("Predictions")
# Set the index of the predictions to the corresponding dates from the forecast
prophet_predictions.index = forecast.ds[-12:]
# Display the predictions
prophet_predictions
# ----------------------------------------------------------------
# Save Future Predictions
# ----------------------------------------------------------------
futture_model_output = pd.DataFrame({
"Date": forecast.ds[-12:].values,
"Transaction Service": transaction_service,
"total": forecast.yhat[-12:].values,
"Model": "Prophet"
})
future_predictions.append(futture_model_output)
# ----------------------------------------
# Save Test Predictions
# ----------------------------------------
model_output = pd.DataFrame({
"Date": Prophet_test_set['ds'].values,
"Transaction Service": transaction_service,
"total": predictions_prophet_tuned.values,
"Model": "Prophet"
})
all_results.append(model_output)
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{'changepoint_prior_scale': 0.5, 'seasonality_mode': 'multiplicative', 'seasonality_prior_scale': 10}
12:51:12 - cmdstanpy - INFO - Chain [1] start processing 12:51:13 - cmdstanpy - INFO - Chain [1] done processing c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\sklearn\metrics\_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn(
The MAE is 208170.79 The RMSE is 273195.40 The MAPE is 4.95 %
12:51:13 - cmdstanpy - INFO - Chain [1] start processing 12:51:14 - cmdstanpy - INFO - Chain [1] done processing
XGBOOST - Machine Learning Model¶
In [10]:
if XGBOOST_Model == True: # Run this section only if XGBoost is enabled in the config
# ----------------------------------------
# 1. Prepare dataset for XGBoost
# ----------------------------------------
# Create a copy of the main dataframe
df_XGboost = df[['ds', 'y']].copy()
# Convert the date column to datetime format
df_XGboost['ds'] = pd.to_datetime(df_XGboost['ds'])
# Set the date column as the index
df_XGboost.set_index('ds', inplace=True)
# Create time-based features so the model can learn seasonal patterns
df_XGboost['quarter'] = df_XGboost.index.quarter # Quarter of the year (1–4)
df_XGboost['month'] = df_XGboost.index.month # Month number (1–12)
df_XGboost['year'] = df_XGboost.index.year # Year
df_XGboost['dayofyear'] = df_XGboost.index.dayofyear # Day of the year
# Create a sequential index to help the model learn
df_XGboost['month_index'] = np.arange(len(df_XGboost))
# Create lag features (previous values) to capture historical patterns
# adding past values of the target variable as new columns so the model can learn from history.
df_XGboost['lag1'] = df_XGboost['y'].shift(12) # Value from 12 months ago
df_XGboost['lag2'] = df_XGboost['y'].shift(24) # Value from 24 months ago
df_XGboost['lag3'] = df_XGboost['y'].shift(36) # Value from 36 months ago
# Remove rows where lag values are missing
df_XGboost = df_XGboost.dropna(subset=['lag1', 'lag2', 'lag3'])
# Define input features (X) and the target variable (y)
FEATURES = ['quarter', 'month', 'year', 'dayofyear', 'month_index', 'lag1', 'lag2', 'lag3']
TARGET = 'y'
# ----------------------------------------
# 2. Time Series Cross Validation
# ----------------------------------------
# Create time-series splits to evaluate the model
tscv = TimeSeriesSplit(n_splits=3, test_size=12)
# Loop through each split to train and validate the model
for train_idx, val_idx in tscv.split(df_XGboost):
# Create training and validation datasets
X_train = df_XGboost.iloc[train_idx][FEATURES]
y_train = df_XGboost.iloc[train_idx][TARGET]
X_val = df_XGboost.iloc[val_idx][FEATURES]
y_val = df_XGboost.iloc[val_idx][TARGET]
# Define the XGBoost model
model = xgb.XGBRegressor(
n_estimators=1000, # Maximum number of trees
early_stopping_rounds=100, # Stop if validation score stops improving
objective='reg:squarederror',
max_depth=4, # Maximum depth of each tree
learning_rate=0.01
)
# Train the model using the training data and evaluate on test data
model.fit(X_train, y_train, eval_set=[(X_val, y_val)], verbose=False)
# ----------------------------------------
# 3. Train Final Model and Test Performance
# ----------------------------------------
# split test and train
df_train = df_XGboost.iloc[:-testing_Periods]
df_test = df_XGboost.iloc[-testing_Periods:]
# Split training and test data into features (X) and target (y)
X_train = df_train[FEATURES]
y_train = df_train[TARGET]
X_test = df_test[FEATURES]
y_test = df_test[TARGET]
# Train the final XGBoost model using the full training dataset
reg_final = xgb.XGBRegressor(
n_estimators=1000,
early_stopping_rounds=100,
objective='reg:squarederror',
max_depth=10,
learning_rate=0.01
)
# Fit the final model and evaluate performance on the test set
reg_final.fit(X_train, y_train, eval_set=[(X_test, y_test)])
# Make predictions on the test data
y_pred_test = reg_final.predict(X_test)
# Calculate RMSE to measure prediction accuracy
XGboost_RMSE_Result = np.sqrt(mean_squared_error(y_test, y_pred_test))
# ----------------------------------------
# 4. Model Evaluation
# ----------------------------------------
# Plot a chart comparing training data, test data, and model predictions
plot_chart(
train=df_train,
test=df_test,
predictions=pd.Series(y_pred_test, index=df_test.index),
title="Test vs Train (XGBoost)"
)
# Calculate Mean Absolute Error (average absolute difference between prediction and actual)
mae = mean_absolute_error(df_test['y'], y_pred_test)
# Calculate Root Mean Squared Error (penalises larger prediction errors)
rmse = mean_squared_error(df_test['y'], y_pred_test, squared=False)
# Calculate Mean Absolute Percentage Error (error expressed as a percentage)
mape = mean_absolute_percentage_error(df_test['y'], y_pred_test) * 100
# Print evaluation results to the console
print(f"The MAE is {mae:.2f}")
print(f"The RMSE is {rmse:.2f}")
print(f"The MAPE is {mape:.2f} %")
# Store RMSE value for later model comparison
XGboost_RMSE_Result = np.sqrt(mean_squared_error(y_test, y_pred_test))
# Save model performance metrics to the results list
model_metrics.append({
"Model": "XGBoost",
"MAE": mae,
"RMSE": rmse,
"MAPE (%)": mape
})
# ----------------------------------------
# 5. Forecast Future Values (Recursive Forecasting)
# ----------------------------------------
# Create future dates to generate forecasts for
future_dates = pd.date_range(
df_XGboost.index.max() + pd.DateOffset(months=1),
periods=forcast_periods,
freq="MS"
)
# Copy historical dataset so predictions can be added during forecasting
history = df_XGboost.copy()
# Creates an empty list to store each future prediction as the model generates them.
future_predictions_list = []
# Loop through each future date to generate predictions
# The model predicts one month at a time.
for date in future_dates:
# Get lag values safely from history (previous months/years)
# used as input features for the prediction.
lag1 = history["y"].iloc[-12] if len(history) >= 12 else history["y"].iloc[-1]
lag2 = history["y"].iloc[-24] if len(history) >= 24 else history["y"].iloc[-1]
lag3 = history["y"].iloc[-36] if len(history) >= 36 else history["y"].iloc[-1]
# Create feature row for the future date
X_future = pd.DataFrame({
"quarter": [date.quarter],
"month": [date.month],
"year": [date.year],
"dayofyear": [date.dayofyear],
"month_index": [history["month_index"].max() + 1],
"lag1": [lag1],
"lag2": [lag2],
"lag3": [lag3]
})
# Predict the value for the next time step
pred = reg_final.predict(X_future)[0]
# Store prediction
future_predictions_list.append(pred)
# Add prediction back into history so future predictions can use it as a lag
new_row = pd.DataFrame({
"y": [pred],
"quarter": [date.quarter],
"month": [date.month],
"year": [date.year],
"dayofyear": [date.dayofyear],
"month_index": [history["month_index"].max() + 1],
"lag1": [lag1],
"lag2": [lag2],
"lag3": [lag3]
}, index=[date])
# Update history with the new prediction
history = pd.concat([history, new_row])
# Create a dataframe containing all future predictions
future_df = pd.DataFrame({
"prediction": future_predictions_list
}, index=future_dates)
# Plot the full forecast
plot_chart(
data=df_XGboost,
train=df_train,
test=df_test,
predictions=future_df["prediction"],
title='XGBoost Forecast and Test Evaluation'
)
# ----------------------------------------
# 6. Save Future Predictions
# ----------------------------------------
# Store future forecast results in a dataframe
futture_model_output = pd.DataFrame({
"Date": future_df.index,
"Transaction Service": transaction_service,
"total": future_df['prediction'].values,
"Model": "XGBoost"
})
# Add the forecast results to the list of future predictions
future_predictions.append(futture_model_output)
# ----------------------------------------
# 7. Save Test Predictions
# ----------------------------------------
# Store model predictions for the test period
model_output = pd.DataFrame({
"Date": df_test.index,
"Transaction Service": transaction_service,
"total": y_pred_test,
"Model": "XGBoost"
})
# Add test predictions to the results list
all_results.append(model_output)
[0] validation_0-rmse:411447.19014 [1] validation_0-rmse:408690.64640 [2] validation_0-rmse:405966.13996 [3] validation_0-rmse:403273.34603 [4] validation_0-rmse:400612.11373 [5] validation_0-rmse:397982.21929 [6] validation_0-rmse:395383.45259 [7] validation_0-rmse:392815.57444 [8] validation_0-rmse:390226.14774 [9] validation_0-rmse:387667.78586 [10] validation_0-rmse:385190.64988 [11] validation_0-rmse:382693.05290 [12] validation_0-rmse:380193.37755 [13] validation_0-rmse:377733.25705 [14] validation_0-rmse:375324.88861 [15] validation_0-rmse:372875.35479 [16] validation_0-rmse:370503.11457 [17] validation_0-rmse:368112.85597 [18] validation_0-rmse:365820.29768 [19] validation_0-rmse:363534.07584 [20] validation_0-rmse:361230.86693 [21] validation_0-rmse:359023.08914 [22] validation_0-rmse:356777.08375 [23] validation_0-rmse:354603.03367 [24] validation_0-rmse:352413.52122 [25] validation_0-rmse:350316.09272 [26] validation_0-rmse:348224.03639 [27] validation_0-rmse:346117.36790 [28] validation_0-rmse:344038.31811 [29] validation_0-rmse:341989.86960 [30] validation_0-rmse:339865.37413 [31] validation_0-rmse:337767.63832 [32] validation_0-rmse:335735.47711 [33] validation_0-rmse:333749.04261 [34] validation_0-rmse:331729.14045 [35] validation_0-rmse:329735.15415 [36] validation_0-rmse:327804.01634 [37] validation_0-rmse:325917.61590 [38] validation_0-rmse:323999.22757 [39] validation_0-rmse:322141.84818 [40] validation_0-rmse:320328.46298 [41] validation_0-rmse:318484.09088 [42] validation_0-rmse:316698.83570 [43] validation_0-rmse:314903.09991 [44] validation_0-rmse:313184.58767 [45] validation_0-rmse:311469.84818 [46] validation_0-rmse:309745.30203 [47] validation_0-rmse:308099.79042 [48] validation_0-rmse:306623.91724 [49] validation_0-rmse:305198.97222 [50] validation_0-rmse:303761.60063 [51] validation_0-rmse:302343.45936 [52] validation_0-rmse:300974.49461 [53] validation_0-rmse:299593.71549 [54] validation_0-rmse:298328.60829 [55] validation_0-rmse:296863.64879 [56] validation_0-rmse:295633.84028 [57] validation_0-rmse:294421.22338 [58] validation_0-rmse:293225.68255 [59] validation_0-rmse:291835.44847 [60] validation_0-rmse:290673.73991 [61] validation_0-rmse:289528.55150 [62] validation_0-rmse:288192.70314 [63] validation_0-rmse:287080.35231 [64] validation_0-rmse:285983.88812 [65] validation_0-rmse:284792.69644 [66] validation_0-rmse:283604.70813 [67] validation_0-rmse:282433.67774 [68] validation_0-rmse:281387.06150 [69] validation_0-rmse:280249.28915 [70] validation_0-rmse:279127.94372 [71] validation_0-rmse:278022.81751 [72] validation_0-rmse:276933.75963 [73] validation_0-rmse:275976.13248 [74] validation_0-rmse:274918.37952 [75] validation_0-rmse:273876.22528 [76] validation_0-rmse:272849.42091 [77] validation_0-rmse:271932.39476 [78] validation_0-rmse:270936.52280 [79] validation_0-rmse:270153.31833 [80] validation_0-rmse:269199.96357 [81] validation_0-rmse:268248.69688 [82] validation_0-rmse:267420.35202 [83] validation_0-rmse:266498.42817 [84] validation_0-rmse:265797.09371 [85] validation_0-rmse:264903.78820 [86] validation_0-rmse:264024.14387 [87] validation_0-rmse:263229.04014 [88] validation_0-rmse:262451.56241 [89] validation_0-rmse:261541.03424 [90] validation_0-rmse:260798.10448 [91] validation_0-rmse:259924.90995 [92] validation_0-rmse:259198.31659 [93] validation_0-rmse:258487.91715 [94] validation_0-rmse:257715.93110 [95] validation_0-rmse:257037.00452 [96] validation_0-rmse:256471.27304 [97] validation_0-rmse:255822.93500 [98] validation_0-rmse:255256.16894 [99] validation_0-rmse:254545.47062 [100] validation_0-rmse:253938.28540 [101] validation_0-rmse:253211.24247 [102] validation_0-rmse:252633.48181 [103] validation_0-rmse:252069.96477 [104] validation_0-rmse:251390.06865 [105] validation_0-rmse:250854.74472 [106] validation_0-rmse:250454.49360 [107] validation_0-rmse:249946.23512 [108] validation_0-rmse:249451.39274 [109] validation_0-rmse:248969.74342 [110] validation_0-rmse:248550.36035 [111] validation_0-rmse:247971.85526 [112] validation_0-rmse:247540.43794 [113] validation_0-rmse:247122.54006 [114] validation_0-rmse:246411.05213 [115] validation_0-rmse:245824.22501 [116] validation_0-rmse:245312.05077 [117] validation_0-rmse:244743.65915 [118] validation_0-rmse:244179.43622 [119] validation_0-rmse:243626.50104 [120] validation_0-rmse:243066.15071 [121] validation_0-rmse:242412.18970 [122] validation_0-rmse:241881.55822 [123] validation_0-rmse:241358.55040 [124] validation_0-rmse:240729.11448 [125] validation_0-rmse:240433.32036 [126] validation_0-rmse:240203.38835 [127] validation_0-rmse:239928.33466 [128] validation_0-rmse:239656.46854 [129] validation_0-rmse:239401.13156 [130] validation_0-rmse:239154.13996 [131] validation_0-rmse:238808.88641 [132] validation_0-rmse:238582.34902 [133] validation_0-rmse:238266.08338 [134] validation_0-rmse:238049.98947 [135] validation_0-rmse:237938.46937 [136] validation_0-rmse:237738.95183 [137] validation_0-rmse:237547.95046 [138] validation_0-rmse:237510.31123 [139] validation_0-rmse:237430.66874 [140] validation_0-rmse:237212.07342 [141] validation_0-rmse:237054.13206 [142] validation_0-rmse:236853.72574 [143] validation_0-rmse:236648.39187 [144] validation_0-rmse:236540.54121 [145] validation_0-rmse:236352.47143 [146] validation_0-rmse:236329.01169 [147] validation_0-rmse:236311.64016 [148] validation_0-rmse:236344.14710 [149] validation_0-rmse:236199.07981 [150] validation_0-rmse:236189.07366 [151] validation_0-rmse:236195.86219 [152] validation_0-rmse:236206.53229 [153] validation_0-rmse:236213.47381 [154] validation_0-rmse:236245.86751 [155] validation_0-rmse:236370.34117 [156] validation_0-rmse:236498.84854 [157] validation_0-rmse:236640.12543 [158] validation_0-rmse:236776.55983 [159] validation_0-rmse:236925.06033 [160] validation_0-rmse:236851.07740 [161] validation_0-rmse:236789.09819 [162] validation_0-rmse:236724.88520 [163] validation_0-rmse:236839.63209 [164] validation_0-rmse:236950.84178 [165] validation_0-rmse:237074.48984 [166] validation_0-rmse:237194.60621 [167] validation_0-rmse:237318.97086 [168] validation_0-rmse:237455.77349 [169] validation_0-rmse:237596.59680 [170] validation_0-rmse:237740.87676 [171] validation_0-rmse:237881.57505 [172] validation_0-rmse:238033.22127 [173] validation_0-rmse:238181.56283 [174] validation_0-rmse:238341.46133 [175] validation_0-rmse:238504.78755 [176] validation_0-rmse:238671.53805 [177] validation_0-rmse:238841.55264 [178] validation_0-rmse:239013.47815 [179] validation_0-rmse:239182.83094 [180] validation_0-rmse:239355.27374 [181] validation_0-rmse:239538.13695 [182] validation_0-rmse:239723.88817 [183] validation_0-rmse:239912.44576 [184] validation_0-rmse:240097.01789 [185] validation_0-rmse:240284.07860 [186] validation_0-rmse:240473.57300 [187] validation_0-rmse:240665.13032 [188] validation_0-rmse:240859.59105 [189] validation_0-rmse:241055.69684 [190] validation_0-rmse:241254.81626 [191] validation_0-rmse:241455.08918 [192] validation_0-rmse:241657.22078 [193] validation_0-rmse:241862.82120 [194] validation_0-rmse:242068.81199 [195] validation_0-rmse:242276.57209 [196] validation_0-rmse:242488.16646 [197] validation_0-rmse:242708.96193 [198] validation_0-rmse:242783.61275 [199] validation_0-rmse:242858.56300 [200] validation_0-rmse:242936.77472 [201] validation_0-rmse:243012.38221 [202] validation_0-rmse:243088.15667 [203] validation_0-rmse:243167.69388 [204] validation_0-rmse:243381.88676 [205] validation_0-rmse:243458.76454 [206] validation_0-rmse:243539.78985 [207] validation_0-rmse:243508.05492 [208] validation_0-rmse:243466.23116 [209] validation_0-rmse:243548.64772 [210] validation_0-rmse:243513.69973 [211] validation_0-rmse:243782.10754 [212] validation_0-rmse:244046.15429 [213] validation_0-rmse:244315.10240 [214] validation_0-rmse:244589.59437 [215] validation_0-rmse:244871.09690 [216] validation_0-rmse:245136.42390 [217] validation_0-rmse:245406.37626 [218] validation_0-rmse:245684.31497 [219] validation_0-rmse:245960.46957 [220] validation_0-rmse:246246.65518 [221] validation_0-rmse:246537.36390 [222] validation_0-rmse:246828.22907 [223] validation_0-rmse:247119.04197 [224] validation_0-rmse:247398.23651 [225] validation_0-rmse:247689.24069 [226] validation_0-rmse:248017.82920 [227] validation_0-rmse:248331.59767 [228] validation_0-rmse:248644.72660 [229] validation_0-rmse:248946.03093 [230] validation_0-rmse:249257.87489 [231] validation_0-rmse:249569.07912 [232] validation_0-rmse:249876.54974 [233] validation_0-rmse:250182.24972 [234] validation_0-rmse:250505.49967 [235] validation_0-rmse:250813.83863 [236] validation_0-rmse:251114.84885 [237] validation_0-rmse:251417.74215 [238] validation_0-rmse:251723.89086 [239] validation_0-rmse:252029.28994 [240] validation_0-rmse:252333.78985 [241] validation_0-rmse:252633.74651 [242] validation_0-rmse:252947.20629 [243] validation_0-rmse:253245.77595 [244] validation_0-rmse:253543.60198 [245] validation_0-rmse:253836.89753 [246] validation_0-rmse:254133.14307 [247] validation_0-rmse:254428.62726 [248] validation_0-rmse:254720.59851 [249] validation_0-rmse:255010.78811
c:\Users\WilcoxJo\AppData\Local\anaconda3\envs\UniForecast\Lib\site-packages\sklearn\metrics\_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn(
The MAE is 181856.00 The RMSE is 236189.07 The MAPE is 4.33 %
Model Results and Outputs¶
In [11]:
# ----------------------------------------
# Store RMSE Scores in a Comparison Table
# ----------------------------------------
# Create a DataFrame to hold RMSE scores for each model
rmse_summary = pd.DataFrame({
'Model': ['Holt-Winters', 'ARIMA', 'Prophet', 'XGBoost'],
'RMSE': [HW_RMSE_Score, Arima_Score, Prophet_RMSE_Result, XGboost_RMSE_Result]
})
# Identify the model with the lowest RMSE
# idxmin() returns the index of the smallest RMSE value
best_model = rmse_summary.loc[rmse_summary["RMSE"].idxmin(), "Model"]
# ----------------------------------------
# Output Test Predictions
# ----------------------------------------
# Combiine all model predictions from list in list
test_results = pd.concat(all_results, ignore_index=True)
# Add a flag column to the final output dataset
# If the row's model matches the best model, flag = 1, otherwise 0
test_results["Best_Model_Flag"] = (test_results["Model"] == best_model).astype(int)
#Output model test data to csv
test_results.to_csv(Output_path + 'test_v_actual/' + transaction_service + '_test_v_actual.csv', index=False)
# ----------------------------------------
# Output all Predictions
# ----------------------------------------
# Combiine all model predictions from list in list
final_predictions = pd.concat(future_predictions, ignore_index=True)
# Add a flag column to the final output dataset
# If the row's model matches the best model, flag = 1, otherwise 0
final_predictions["Best_Model_Flag"] = (final_predictions["Model"] == best_model).astype(int)
#Output model predictions to csv
final_predictions.to_csv(Output_path + 'predictions/' + transaction_service + '_model_predictions.csv', index=False)
model_results = pd.DataFrame(model_metrics)
# Flag best model
model_results["Best_Model"] = (model_results["RMSE"] == model_results["RMSE"].min()).astype(int)
# Print model results
model_results
#Output model results to csv
model_results.to_csv(Output_path + 'model_evaluation_results/' + transaction_service + '_model_evaluation_results.csv', index=False)
# Print model results
model_results
Out[11]:
| Model | MAE | RMSE | MAPE (%) | Best_Model | |
|---|---|---|---|---|---|
| 0 | ARIMA | 275652.883647 | 327019.875374 | 6.842363 | 0 |
| 1 | Prophet | 208170.794651 | 273195.402855 | 4.947856 | 0 |
| 2 | XGBoost | 181856.000000 | 236189.073709 | 4.333464 | 1 |