Time Series Forecasting in Python

11 Capstone: Forecasting the number of antidiabetic drug prescriptions in Australia

This chapter covers

• Developing a forecasting model to predict the number of antidiabetic drug prescriptions in Australia
• Applying the modeling procedure with a SARIMA model
• Evaluating our model against a baseline
• Determining the champion model

We have covered a lot of statistical models for time series forecasting. Back in chapters 4 and 5, you learned how to model moving average processes and autoregressive processes. We then combined these models to form the ARMA model and added a parameter to forecast non-stationary time series, leading us to the ARIMA model. We then added a seasonal component with the SARIMA model. Adding the effect of exogenous variables ...