hello, are there functions to detecte outlying observations in samples? thanks. ___________________________________________________________________________ [[alternative HTML version deleted]]
Hi It often depends on your attitude to limits for outlying observations. Boxplot has some identifying routine for selecting outlying points. Any procedure usually requires somebody to choose which observation is outlying and why. You can use e.g. all values which are beyond some threshold based on sd but that holds only if distribution is normal. set.seed(1) x<-rnorm(x) ul <- mean(x) +3*sd(x) ll <- mean(x) -3*sd(x) beyond <- (x>ul) | ( x <ll)> x[beyond][1] 3.810277 Regards Petr petr.pikal at precheza.cz r-help-bounces at stat.math.ethz.ch napsal dne 19.06.2007 11:29:17:> hello, > are there functions to detecte outlying observations in samples? > thanks. > > > > > > > > >___________________________________________________________________________> > > > > > [[alternative HTML version deleted]] > > ______________________________________________ > R-help at stat.math.ethz.ch mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guidehttp://www.R-project.org/posting-guide.html> and provide commented, minimal, self-contained, reproducible code.
r-help-bounces at stat.math.ethz.ch napsal dne 19.06.2007 12:23:58:> Hi > > It often depends on your attitude to limits for outlying observations. > Boxplot has some identifying routine for selecting outlying points. > > Any procedure usually requires somebody to choose which observation is > outlying and why. You can use e.g. all values which are beyond some > threshold based on sd but that holds only if distribution is normal. > > set.seed(1) > x<-rnorm(x)Sorry, it shall be x <- rnorm(1000)> ul <- mean(x) +3*sd(x) > ll <- mean(x) -3*sd(x) > beyond <- (x>ul) | ( x <ll) > > > x[beyond] > [1] 3.810277 > > Regards > Petr > > petr.pikal at precheza.cz > > r-help-bounces at stat.math.ethz.ch napsal dne 19.06.2007 11:29:17: > > > hello, > > are there functions to detecte outlying observations in samples? > > thanks. > > > > > > > > > > > > > > > > > > >___________________________________________________________________________> > > > > > > > > > > > [[alternative HTML version deleted]] > > > > ______________________________________________ > > R-help at stat.math.ethz.ch mailing list > > https://stat.ethz.ch/mailman/listinfo/r-help > > PLEASE do read the posting guide > http://www.R-project.org/posting-guide.html > > and provide commented, minimal, self-contained, reproducible code. > > ______________________________________________ > R-help at stat.math.ethz.ch mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guidehttp://www.R-project.org/posting-guide.html> and provide commented, minimal, self-contained, reproducible code.
You might want to have a look at the outliers package on CRAN. --- elyakhlifi mustapha <elyakhlifi_mustapha at yahoo.fr> wrote:> hello, > are there functions to detecte outlying observations > in samples? > thanks. > > > > > > > > >___________________________________________________________________________> > > > > > [[alternative HTML version deleted]] > > ______________________________________________ > R-help at stat.math.ethz.ch mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide > http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, > reproducible code. >
check package dprep On 6/19/07, elyakhlifi mustapha <elyakhlifi_mustapha at yahoo.fr> wrote:> hello, > are there functions to detecte outlying observations in samples? > thanks. > > > > > > > > > ___________________________________________________________________________ > > > > > > [[alternative HTML version deleted]] > > ______________________________________________ > R-help at stat.math.ethz.ch mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code. >-- Weiwei Shi, Ph.D Research Scientist GeneGO, Inc. "Did you always know?" "No, I did not. But I believed..." ---Matrix III
At 05:29 AM 6/19/2007, elyakhlifi wrote:>hello, >are there functions to detecte outlying observations in samples? >thanks.library('car') ? outlier.test library('outliers') ? grubbs.test ? dixon.test ? cochran.test ? chisq.out.test ===============================================================Robert A. LaBudde, PhD, PAS, Dpl. ACAFS e-mail: ral at lcfltd.com Least Cost Formulations, Ltd. URL: http://lcfltd.com/ 824 Timberlake Drive Tel: 757-467-0954 Virginia Beach, VA 23464-3239 Fax: 757-467-2947 "Vere scire est per causas scire"