Implementations in Statistics Packages
Various packages that apply methodology like Box-Jenkins parameter optimization are available to find the right parameters for the ARIMA model.
- In R, the standard stats package includes an arima function, is documented in "ARIMA Modelling of Time Series". Besides the ARIMA(p,d,q) part, the function also includes seasonal factors, an intercept term, and exogenous variables (xreg, called "external regressors"). The CRAN task view on Time Series is the reference with many more links.
- The "forecast" package in R can automatically select an ARIMA model for a given time series with the auto.arima function. The package can also simulate seasonal and non-seasonal ARIMA models with its simulate.Arima function. It also has a function Arima, which is a wrapper for the arima from the "stats" package.
- SAS(R) of "SAS Institute Inc." includes extensive ARIMA processing in its Econometric and Time Series Analysis system: SAS/ETS.
- Stata includes ARIMA modelling (using its arima command) as of Stata 9.
- SAP(R) "SAP" allows creating models like ARIMA by using native, predictive algorithms and by employing algorithms from R.
Read more about this topic: Autoregressive Integrated Moving Average
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