Hi Hans - I tried your suggestion and it worked out well... Many thanks!! Also, thank to everyone else for their suggestions.
Hans W. Borchers-4 wrote: > > 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. > > -- View this message in context: http://www.nabble.com/Outlier-Detection-for-timeseries-tp22008448p22017808.html Sent from the R help mailing list archive at Nabble.com. ______________________________________________ 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.