Fits an autoregressive integrated moving-average (ARIMA) model to time-series data. The series and results
can be displayed graphically and forecasts of future observations can be formed.
Series
Specifies a variate containing the time series data.
ARIMA Model
Specifies the model to be fitted, using the Box-Jenkins ARIMA notation. You
need to supply the orders for the model, that is, the number of parameters for the autoregressive and moving-average
parts of the model, and the degree of differencing required. You can also specify whether the constant term should be
fixed at a given value or estimated, and whether a Box-Cox transformation should be applied to the data before analysis using
either a fixed value or estimating the optimal transformation. The default action is to fix the Box-Cox parameter
to 1, i.e. no transformation.
Available Data
This lists variates that can be used as the Series data. Double-click on a name to copy it to the Series
field; alternatively, you can type in the name directly.
See Also
- Options for controlling what statistics are displayed
- Seasonal Model for including seasonal components in the model
- Further Output for additional printing and plotting of results
- Save for saving the results from an ARIMA analysis Forecasts for generating forecasts from the fitted model