8. General Forecasting

Forecasting procedure

1. Choose a model
2. Split data into train and test sets
3. Fit model on training set
4. Evaluate model on test set
5. Re-fit model on entire data set
6. Forecast for future data

Contents: 8.1 Introduction to Forecasting Models Part 1 8.2 Evaluating Forecast Predictions 8.3 Introduction to Forecasting Models Part 2 8.4 ACF and PACF Theory 8.5 ACF and PACF Code Along 8.6 ARIMA Overview 8.7 Autoregression - AR - Overview 8.8 Autoregression - AR with Statmodels 8.9 Descriptive Statistics and Tests - Part 1 8.10 Descriptive Statistics and Tests - Part 2 8.11 Descriptive Statistics and Tests - Part 3 8.12 Arima Theory Overview 8.13 Choosing ARIMA Orders - Part 1 8.13 Choosing ARIMA Orders - Part 2 8.14 ARMA and ARIMA - AutoRegressive Integrated Moving Average - Part 1 8.14 ARMA and ARIMA - AutoRegressive Integrated Moving Average - Part 2 8.15. SARIMA - Seasonal Autoregressive Integrated Moving Average 8.16 SARIMAX - Seasonal Autoregressive Integrated Moving Average Exogenous - Part 1 8.17 SARIMAX - Seasonal Autoregressive Integrated Moving Average Exogenous - Part 2