Pele <drdionc <at> yahoo.com> writes: > > > Hello R users, > > Can someone tell if there is a package in R that can do outlier detection > that give outputs simiilar to what I got from SAS below. > > Many thanks in advance for any help!
I guess you are talking about the OUTLIER procedure in SAS that attempts to detect 'additive outliers' and 'level shifts' in a 'response' series, the second following Jong & Penzer's "Diagnosing shocks in time series". I have not come across this method in R, but you might have a look into the 'robfilter' (Robust Time Series Filters) package with functions like 'dw.filter', 'adore.filter', or 'wrm.filter', see for instance "dw.filter is suitable for extracting low frequency components (the signal) from a time series which may be contaminated with outliers and can contain level shifts. For this, moving window techniques are applied." If your time series is actually a response, you might prefer to look at the series of residuals instead. > Outlier Details > > Approx > Chi- > Prob> > Obs Time ID Type Estimate Square > ChiSq > > 12 12.000000 Additive 2792544.6 186.13 > <.0001 > 13 13.000000 Additive 954302.1 21.23 > <.0001 > 15 15.000000 Shift 63539.3 > 9.06 0.0026 > ______________________________________________ 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.