ARIMA models are also referred to as Box-Jenkins models, owing to the approach made popular by the statisticians George Box and Gwilym Jenkins. It is worth noting that along with ARIMA, there are other terms, such as AR, MA, and ARMA, which help to form the ARIMA approach. George Box and Gwilym Jenkins are remembered for their contributions, as they bought together the AR and the MA approach. The ARIMA approach was developed in three parts. Let's first explore why ARIMA is relevant to time series forecasting. We can then focus on understanding the nuances of ARIMA.
One of the reasons we want to use ARIMA is to compare our multivariate model to a different methodology. We do occasionally see multivariate regression used for forecasting ...
