Dear Rado, First I would do is to investigate the data I consider "outliers"; it brings some consequences to exclude them IF the data are naturally occur, and it means we lost them, otherwise we can exclude them. However, I don't think you need a sophisticated way to do that since you can run analyses like stepwise or robust analysis. Exclude one by one, and run your analysis to see how far the exclusion will impact to your results, do this repeatedly. This is to avoid exclusion "valuable" data and important information in every single data you have... Alternatively, you can read Tukey's book " Exploratory Data analysis", I don't have it now. Cheers, Eduwin -----Original Message----- From: owner-r-help at stat.math.ethz.ch [mailto:owner-r-help at stat.math.ethz.ch] On Behalf Of Rado Bonk Sent: Tuesday, November 26, 2002 10:36 PM To: r-help at stat.math.ethz.ch Subject: [R] how to identify the outliers 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 -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-. -.-.-.- r-help mailing list -- Read http://www.ci.tuwien.ac.at/~hornik/R/R-FAQ.html Send "info", "help", or "[un]subscribe" (in the "body", not the subject !) To: r-help-request at stat.math.ethz.ch _._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._. _._._._ -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list -- Read http://www.ci.tuwien.ac.at/~hornik/R/R-FAQ.html Send "info", "help", or "[un]subscribe" (in the "body", not the subject !) To: r-help-request at stat.math.ethz.ch _._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._