Plot Method for "lmrob" Objects
Diagnostic plots for elements of class lmrob
## S3 method for class 'lmrob'
plot(x, which = 1:5,
caption = c("Standardized residuals vs. Robust Distances",
"Normal Q-Q vs. Residuals", "Response vs. Fitted Values",
"Residuals vs. Fitted Values" , "Sqrt of abs(Residuals) vs. Fitted Values"),
panel = if(add.smooth) panel.smooth else points,
sub.caption = deparse(x$call), main = "",
compute.MD = TRUE,
ask = prod(par("mfcol")) < length(which) && dev.interactive(),
id.n = 3, labels.id = names(residuals(x)), cex.id = 0.75,
label.pos = c(4,2), qqline = TRUE, add.smooth = getOption("add.smooth"),
..., p=0.025)x |
an object as created by |
which |
integer number between 1 and 5 to specify which plot is desired |
caption |
Caption for the different plots |
panel |
panel function. The useful alternative to
|
main |
main title |
sub.caption |
sub titles |
compute.MD |
logical indicating if the robust Mahalanobis
distances should be recomputed, using |
ask |
waits for user input before displaying each plot |
id.n |
number of points to be labelled in each plot, starting with the most extreme. |
labels.id |
vector of labels, from which the labels for extreme
points will be chosen. |
cex.id |
magnification of point labels. |
label.pos |
positioning of labels, for the left half and right half of the graph respectively. |
if compute.MD = TRUE and the robust Mahalanobis distances need
to be computed, they are stored (“cached”) with the object
x when this function has been called from top-level.
Robust diagnostic plots as in Rousseeuw and van Zomeren (1990), see
‘References’ in ltsPlot.
data(starsCYG) ## Plot simple data and fitted lines plot(starsCYG) lmST <- lm(log.light ~ log.Te, data = starsCYG) RlmST <- lmrob(log.light ~ log.Te, data = starsCYG) RlmST abline(lmST, col = "red") abline(RlmST, col = "blue") op <- par(mfrow = c(2,2), mgp = c(1.5, 0.6, 0), mar= .1+c(3,3,3,1)) plot(RlmST, which = c(1:2, 4:5)) par(op)
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