Forward Search in Linear Regression

Description

This function plots the results of a forward search analysis in linear regression models.

Usage

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## S3 method for class 'fwdlm'
plot(x, which.plots = 1:10, squared = FALSE, scaled = TRUE, 
     ylim = NULL, xlim = NULL, th.Res = 2, th.Lev = 0.25, sig.Tst = 2.58, 
     labels.in.plot = TRUE, ...)

Arguments

x

a "fwdlm" object.

which.plots

select which plots to draw, by default all. Each graph is addressed by an integer:

  1. scaled residuals

  2. leverages

  3. maximum studentized residuals

  4. minimum deletion residuals

  5. coefficients

  6. statistics

  7. forward Cook's distances

  8. modified forward Cook's distances

  9. S^2 values

  10. R^2 values

squared

logical, if TRUE plots squared residuals.

scaled

logical, if TRUE plots scaled coefficient estimates.

ylim

a two component vector for the min and max of the y axis.

xlim

a two component vector for the min and max of the x axis.

th.Res

numerical, a threshold for labelling the residuals.

th.Lev

numerical, a threshold for labelling the leverages.

sig.Tst

numerical, a value (on the scale of the t statistics) used to draw the confidence interval on the plot of the t statistics.

labels.in.plot

logical, if TRUE units are labelled in the plots when required.

...

further arguments passed to or from other methods.

Author(s)

Originally written for S-Plus by: Kjell Konis kkonis@insightful.com and Marco Riani mriani@unipr.it
Ported to R by Luca Scrucca luca@stat.unipg.it

References

Atkinson, A.C. and Riani, M. (2000), Robust Diagnostic Regression Analysis, First Edition. New York: Springer, Chapters 2-3.

See Also

fwdlm, fwdsco, fwdglm.

Examples

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## Not run: data(forbes)
## Not run: plot(forbes)
## Not run: mod <- fwdlm(Log.Pressure ~ Boiling.point, data=forbes)
## Not run: summary(mod)
## Not run: plot(mod)