[R] STL - time series seasonal decomposition sensitive to data points?
sezenismail at gmail.com
Wed Jul 19 20:51:07 CEST 2017
> On 19 Jul 2017, at 21:34, Eridk Poliruyt <ep19772 at 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,
First of all,  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  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.
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