On Fri, Dec 30, 2011 at 9:03 AM, Michael <comtech....@gmail.com> wrote: > Happy holidays all! > > I know it's very subjective to determine whether some data is outlier or > not... > > But are there reasonally good and realistic methods of identifying outliers > in R?
What kind of data do you have? For simple numeric data, there are various methods for removing outliers developed for robust estimation and I'm sure they are implemented in R. For example, this link http://www.unt.edu/benchmarks/archives/2001/december01/rss.htm describes how to calculate a robust measure of correlation that includes a method to downweigh (or remove) outliers. For identifying outlier samples in multivariate setting, the possibilities are even more varied, from simple hierarchical clustering and visual identification of outliers to network connectivity methods etc. HTH, Peter ______________________________________________ R-help@r-project.org 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.
