Hi Stephen, I am doing cross correlation analysis and I am trying to find a outlier detection function in R that can detect changes in the level of the response series that are not accounted for by the estimated model. Something that tells whether the changes are considered Additive Outliers, Level Shifts, or Temporary Changes... The output in the original not is what SAS produces and I was looking for something similar.. R is very new to me (4 weeks) hence still feeling my way around...
Many thanks! Pele wrote: > > 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! > > 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 > > -- View this message in context: http://www.nabble.com/Outlier-Detection-for-timeseries-tp22008448p22012539.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.
