There are two issues here identifying the outliers and highlighting them.
I have only a basic grasp of both of these concepts but will give what I have in
case it helps. There appears to have been a move in the last 2 decades to
improve the concepts of what actually constitutes an outlier, Brian Ripley made
comment on this in 2003 when he said "That's the whole point of robust
methods: compensate rather than reject." So I would suggest that you might
like to find a copy of an article cited by Brian last year
http://finzi.psych.upenn.edu/R/Rhelp02a/archive/35340.html
As Uwe has pointed out if you are using pairs than you will have to write your
own panel function unless someone has already written something. I have avoided
using the panel function as it seems a bit cumbersome in comparison to writing
your own using normal plots.
I haven't used the lattice package for a while now but it is obvious that
major improvements have been made recently and you may find that this is a
better vehicle for plotting your data.
However for a single plot there's no real problem.
plot(x,y,pch = 20, col = "navy")
points(x[outlier],y[outlier],pch = 20, col = "red")
where "outlier" are the observations you consider to be such
A crude example of what can be done rather than what should be done is (I have
used inappropriate data)
par(mfrow = c(4,4))
# Just select setosa
iris <- iris[1:50,]
for (j in 1:4){
for (k in 1:4){
if (j == k){
plot(5,axes = FALSE,type = "n",xlab = "",ylab =
"")
} else {
mah <-
mahalanobis(iris[,c(j,k)],rowMeans(iris[,c(j,k)]),cov(iris[,c(j,k)]))
outlier <- which(mah > quantile(mah,.95))
plot(iris[,j],iris[,k],pch = 20, col = "navy",axes = F,xlab =
names(iris)[j],ylab = names(iris)[k])
points(iris[outlier,j],iris[outlier,k],pch = 20, col = "red")
}
}
}
> -----Original Message-----
> From: Brett Stansfield [mailto:brett at hbrc.govt.nz]
> Sent: Tuesday, 22 March 2005 6:09 AM
> To: R help (E-mail)
> Subject: [R] Highlighting points in a scatter plot matrix
>
>
> Dear R
> I recently did a scatterplot matrix using the following command
> pairs(sleep[c("SlowSleep", "ParaSleep",
"logbw", "logbrw", "loglife",
> "loggest")],col=1+as.integer(ParaSleep > 5.5 | SlowSleep >
15.7))
> this highlighted outlying points for some of the x,y plots
> that I needed to
> identify. Unfortunately this highlights all the x,y plots
> some for which
> these points are not necessarily outliers. Is there a way to specify
> highlighting selected points at selected x,y plots within a matrix?
>
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