Dear Community,
I want to identify outliers in my data. I don't know how to use identify
command in the plots obtained.
I've gone through help files and use mahalanobis example for my purpose:
NormalMultivarianteComparefunc <- function(x) {
Sx <- cov(x)
D2 <- mahalanobis(x, colMeans(x), Sx)
plot(density(D2, bw=.5), main="Squared Mahalanobis distances, n=nrow(x),
p=ncol(x)")
rug(D2)
qqplot(qchisq(ppoints(nrow(x)), df=ncol(x)), D2,
main = expression("Q-Q plot of Mahalanobis" * ~D^2 *
" vs. quantiles of" * ~ chi[ncol(x)]^2))
abline(0, 1, col = 'gray')
}
Then I run:
NormalMultivarianteComparefunc(y); y dataframe with the data. Now, let's say
y =replicate(5, rnorm(100))
##what should I write now to identify data from the plot??
##/identify(y)
warning: no point within 0.25 inches
/ ?????
I know I can use aq.plot, but I would be very grateful if you could help me
with identify.
/By the way, in the function, how can the title write the value of the
variables in spite of "ncol(x)" or "nrow(x)"/
Thanks in advance, u...@host.com
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