plot.wle.lm: Plots for the Linear Model
In wle: Weighted Likelihood Estimation

Description Usage Arguments Author(s) See Also Examples

The plot.wle.lm function plots a separate graph windows for each root. In each windows four plots are printed: residuals vs fitted, normal qq plot of the residuals, weighted residuals vs weighted fitted, normal qq plot of the weighted residuals. A summary plot is also printed: in the diagonal, the value of the weigths vs position of the observations for each root; in the upper diagonal residuals vs residuals of two different roots; in the lower diagonal weights vs weights of two different roots. The roots and the graphs can be chosen by the arguments roots, which.main and which.

## S3 method for class 'wle.lm'
plot(x, roots, which=1:4, which.main, level.weight=0.5, 
   ask = dev.interactive(), col=c(2, 1, 3), id.n=3, labels.id,
   cex.id = 0.75, verbose=FALSE, ...)

`x`	an object of class `wle.lm`.
`roots`	a vector specify for which roots the plots are required.
`which`	if a subset of the plots for each root is required, specify a subset of the numbers `0:4`, 0 means no plots.
`which.main`	if a subset of the plots for the main graphic is required, specify a subset of the numbers `0:roots^2`, 0 means no plots. The plots are specified by columns.
`level.weight`	value of the weight under which an observations is marked with different color.
`ask`	logical; if `TRUE`, the user is asked before each plot, see `par(ask=.)`.
`col`	a vector of 3 elements, to specify colors for the plots.
`id.n`	number of points to be labelled in some plots, starting with the ones with less weight.
`labels.id`	vector of labels, from which the labels for less weighted points will be chosen. If missing uses observation numbers.
`cex.id`	magnification of point labels.
`verbose`	if `TRUE` warnings are printed.
`...`	graphical parameters can be given as arguments.

Claudio Agostinelli

wle.lm a function for estimating linear models with normal distribution error and normal kernel.

library(wle)

data(artificial)

result <- wle.lm(y~x1+x2+x3, data=artificial, boot=40, group=6, num.sol=2)

result

plot(result) # all plots, default behavior 

plot(result, roots=1) # only first root, one plot for window 

par(mfcol=c(2,2))
plot(result, roots=1) # only first root, as usual

plot(result, roots=2, which=1, which.main=0)
# only second root, only residual vs fitted values plot

plot(result, which=1)
# main plot + residual vs fitted values plot for each root

par(mfcol=c(3,2))
plot(result, which=1)
# main plot + residual vs fitted values plot for each root all in the same window