> On 19 Jul 2017, at 21:34, Eridk Poliruyt <ep19...@gmail.com> wrote: > > Hi all, > > I am trying to analyse a time series data and want to make > trend-season decomposition using STL approach in R. However I found > the decomposition result seems to be sensitive to data points even > with the robust option. > > More specifically, suppose I have a few years of monthly data. Using > stl, I got a decomposition T1 + S1 + R1. Then I deleted the most > recent two or three data points, the resulted decomposition T2 + S2 + > R2 are totally different from the one with full data, especially for > the beginning of time series which is weird. I would have expected > that wouldn't be changed much due to the local nature of STL. > > May I ask for any thoughts and help on this issue? Many thanks! > > Best regards, > Eric
Hello Eridk, First of all, [1] might be a better place to ask a statistical questions. Second, (with my limited knowledge) STL simply assumes a steady periodicity and amplitude in the seasonal component. Your data (we don’t know what your data is) might not obey this rule and perhaps it’s not a good approach. Nevertheless, please, create an as much as minimal example to illustrate the situation, ask your question at [1] and please share a link to the question here. Thus, you increase the chance to get an urgent answer and I can also follow the answers to your question. best, ismail 1- https://stats.stackexchange.com ______________________________________________ R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see 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.
