plot.gvlma {gvlma}

Various Plots for a Gvlma Object

Description

Diagnostic plots for a single-response gvlma linear model.

Usage

## S3 method for class 'gvlma'
plot(x, onepage = TRUE, ask = !onepage && prod(par("mfcol")) <
    ncol(model.matrix(x)) + 4 && dev.interactive(), ...)

Arguments

x

A gvlmaobj object.

onepage

If TRUE, all plots will be displayed in one page of graphs.

ask

If TRUE, user will be prompted before plots begin a new page.

...

Additional arguments that are ignored.

Details

A series of plots is generated for diagnostic assessment of a linear model for a single response variable. The plots are similar to those generated by plot.lm. The plots are (a) the response versus each of the predictors in the model, (b) the response versus the time sequence in the gvlma object (gvlmaobj\$GlobalTest\$timeseq), which is the time sequence used for computing the directional test statistic S^2_4, (c) the standardized residuals vs the fitted values, (d) a histogram of the standardized residuals, (e) a normal probability plot of the standardized residuals, and (f) a plot of the standardized residuals versus the time sequence.

Note that the standardized residuals here are computed as the raw residuals divided by the MLE of the error standard deviation (i.e. sqrt(SSE/n)).

Value

No value is returned.

Note

The standardized residuals here are computed as the raw residuals divided by the MLE of the error standard deviation (i.e. sqrt(SSE/n)).

Author(s)

Slate, EH [e-mail] and Pena, EA [e-mail].

References

Pena, EA and Slate, EH (2006). “Global validation of linear model assumptions,” J.\ Amer.\ Statist.\ Assoc., 101(473):341-354.

See Also

gvlma

Examples

data(CarMileageData)
CarModelAssess <- gvlma(NumGallons ~ MilesLastFill + NumDaysBetw,
    data = CarMileageData)
plot(CarModelAssess)
par(mfrow=c(2,2))
plot(CarModelAssess, onepage = FALSE)