how to identify the outliers - R-help

Rado Bonk · 2002-11-26T15:36:11Z

Hello R-users, Is there any more sophisticated way how to identify the dataset outliers other then seeing them in boxplot? I wanna exclude them from further analysis and I am interested in their position in my vector data. Rado -- Radoslav Bonk M.S. Dept. of Physical Geography and Geoecology Faculty of Sciences, Comenius University Mlynska Dolina 842 15, Bratislava, SLOVAKIA tel: +421 2 602 96 250 e-mail: rbonk at host.sk -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-

Christian Hennig

Tue, Nov 26, 2002 8:48 AM #

Dear Rado,

I do not know how your data looks like, but generally you can use robust
Mahalanobis distances. That is, compute robust mean and covariance matrix
by cov.rob (method="mcd") in Library lqs, and put these as center and cov
into the function mahalanobis. As cutoff value you can take a large
quantile (say 0.999) of the chi^2-distribution with p (number of your
variables) degrees of freedom. Details in Rousseeuw & van Driessen, see
help page on cov.rob. 

Christian

On Tue, 26 Nov 2002, Rado Bonk wrote:

***********************************************************************
Christian Hennig
Seminar fuer Statistik, ETH-Zentrum (LEO), CH-8092 Zuerich (currently)
and Fachbereich Mathematik-SPST/ZMS, Universitaet Hamburg
hennig at stat.math.ethz.ch, http://stat.ethz.ch/~hennig/
hennig at math.uni-hamburg.de, http://www.math.uni-hamburg.de/home/hennig/
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ich empfehle www.boag.de


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