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outlier identify in qqplot

2 messages · agent dunham, R. Michael Weylandt

agent dunham
# 
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, user at host.com


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R. Michael Weylandt
# 
Try this

qqInteractive <- function(..., IDENTIFY = TRUE){
     qqplot(...) -> X
     if(IDENTIFY) return(identify(X))
     invisisble(X)
}

The trick is that identify wants coordinates of the point in the
scatter plot which are not the inputs to qqplot() but rather a
transformation thereof.

Michael
On Wed, Nov 16, 2011 at 9:52 AM, agent dunham <crosspide at hotmail.com> wrote: