plot.fwdlm {forward}

Forward Search in Linear Regression

Description

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

Usage

## 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 [e-mail] and Marco Riani [e-mail]
Ported to R by Luca Scrucca [e-mail]

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

library(MASS)
data(forbes)
plot(forbes)
mod <- fwdlm(100*log10(pres) ~ bp, data=forbes)
summary(mod)
## Not run: plot(mod)