The VARMAX Procedure

ODS Graphics

Subsections:

This section describes the use of ODS for creating statistical graphs with the VARMAX procedure.

When ODS GRAPHICS are in effect, the VARMAX procedure produces a variety of plots for each dependent variable.

The plots available are as follows:

  • The procedure displays the following plots for each dependent variable in the MODEL statement with the PLOT= option in the VARMAX statement:

    • impulse response function

    • impulse response of the transfer function

    • time series and predicted series

    • prediction errors

    • distribution of the prediction errors

    • normal quantile of the prediction errors

    • ACF of the prediction errors

    • PACF of the prediction errors

    • IACF of the prediction errors

    • log scaled white noise test of the prediction errors

  • The procedure displays forecast plots for each dependent variable in the OUTPUT statement with the PLOT= option in the VARMAX statement.

ODS Graph Names

The VARMAX procedure assigns a name to each graph it creates by using ODS. You can use these names to reference the graphs when using ODS. The names are listed in Table 35.13.

Table 35.13: ODS Graphics Produced in the VARMAX Procedure

ODS Table Name

Plot Description

Statement

ErrorACFPlot

Autocorrelation function of prediction errors

MODEL

ErrorIACFPlot

Inverse autocorrelation function of prediction errors

MODEL

ErrorPACFPlot

Partial autocorrelation function of prediction errors

MODEL

ErrorDiagnosticsPanel

Diagnostics of prediction errors

MODEL

ErrorNormalityPanel

Histogram and Q-Q plot of prediction errors

MODEL

ErrorDistribution

Distribution of prediction errors

MODEL

ErrorQQPlot

Q-Q plot of prediction errors

MODEL

ErrorWhiteNoisePlot

White noise test of prediction errors

MODEL

ErrorPlot

Prediction errors

MODEL

ModelPlot

Time series and predicted series

MODEL

AccumulatedIRFPanel

Accumulated impulse response function

MODEL

AccumulatedIRFXPanel

Accumulated impulse response of transfer function

MODEL

OrthogonalIRFPanel

Orthogonalized impulse response function

MODEL

SimpleIRFPanel

Simple impulse response function

MODEL

SimpleIRFXPanel

Simple impulse response of transfer function

MODEL

ModelForecastsPlot

Time series and forecasts

OUTPUT

ForecastsOnlyPlot

Forecasts

OUTPUT