Hi,

if Soren is right, why not take a look on the identify help page?

Christian

On Mon, 8 Aug 2005, Søren Højsgaard wrote:

> Perhaps what Alessandro is after is simpler than that: Making a plot of data 
> in a data frame, being able to click on 'suspicious points', getting the 
> corresponding rows of a data out in a new data frame (for further inspection) 
> while keeping the 'good points' in the plot (and perhaps redoing some 
> calculations on the basis of the good points only....). This could then go on 
> in an iterative way. That would be a perfectly sensible thing to do. How 
> difficult it is technically I don't know, but it seems that it would require 
> a call-back mechanism from a plot window to R (and a more 'advanced' one than 
> provided by 'locator()').
>
> Best regards
> Søren
>
> -----Oprindelig meddelelse-----
> Fra: [EMAIL PROTECTED] [mailto:[EMAIL PROTECTED] På vegne af Christian Hennig
> Sendt: 8. august 2005 14:45
> Til: alessandro carletti
> Cc: rHELP
> Emne: Re: [R] selecting outliers
>
> Hi Alessandro,
>
> On Mon, 8 Aug 2005, alessandro carletti wrote:
>
> > Hi everybody,
> > I'd like to know if there's an easy way for extracting outliers record
> > from a dataset, in order to perform further analysis on them.
>
> The answer is "no". The reasons are not technical. There are some quite easy 
> outlier detection approaches around (e.g., compute robust Mahalanobis 
> distances with cov.mcd/mahalanobis and call the points with too large 
> distances "outliers").
> But the main problem is that the term outlier has no objective, unique 
> meaning. It depends crucially on your aims and on the assumptions you want to 
> make about the non-outliers in the dataset (which should be elliptically 
> distributed and homogeneously close to a multivariate normal distribution for 
> the Mahalanobis approach).
>
> Best,
> Christian
>
> *** NEW ADDRESS! ***
> Christian Hennig
> University College London, Department of Statistical Science Gower St., 
> London WC1E 6BT, phone +44 207 679 1698 [EMAIL PROTECTED], 
> www.homepages.ucl.ac.uk/~ucakche
>
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*** NEW ADDRESS! ***
Christian Hennig
University College London, Department of Statistical Science
Gower St., London WC1E 6BT, phone +44 207 679 1698
[EMAIL PROTECTED], www.homepages.ucl.ac.uk/~ucakche

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