Building ARIMA time series models
The term ARIMA is made up of the letters that represent a modeling approach for time series data. ARIMA models contain the following three elements:
- AR: Auto regressive, specified with p or P
- I: Integrated (differencing), specified with d or D
- MA: Moving average, specified with q or Q
Auto regressive means that earlier lagged points in the data influence later points in the sequence. This creates a dependence condition. The type of AR model chosen is based on how many steps away (lags) the points in the past affect the points in the future. Data that has a greater lingering effect on future points has a higher lag. The higher the lag, the higher the AR number. You will see models referred to as AR(1), AR(2), and ...
Get Introduction to R for Business Intelligence now with the O’Reilly learning platform.
O’Reilly members experience books, live events, courses curated by job role, and more from O’Reilly and nearly 200 top publishers.
