What does the stepwise ARIMA model automatically calculate?

The stepwise ARIMA model is designed to automate the process of identifying and estimating the parameters necessary for building an effective time series forecasting model. In particular, it selects the optimal combination of autoregressive, differencing, and moving average parameters based on the patterns observed in the historical data. This includes calculating parameters like the orders of differencing and the coefficients for the autoregressive and moving average components to best fit the data's unique characteristics.

By automating this calculation, the stepwise ARIMA model saves time and reduces the complexity involved in manually determining which parameters to include. It helps ensure that the model created is statistically sound and maximizes predictive accuracy, which is essential for making reliable forecasts in various fields such as economics, supply chain management, and business analytics. Thus, the key feature of the stepwise ARIMA model is its ability to automatically calculate all relevant parameters needed for effective forecasting.