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 ______________________________________________ [email protected] mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
