Hi all,
I have a time series that contains double seasonal components (48 and 336) and I would like to decompose the series into the following time series components (trend, seasonal component 1, seasonal component 2 and irregular component). As far as I know, the STL procedure for decomposing a series in R only allows one seasonal component, so I have tried decomposing the series twice. First, by setting the frequency to be the first seasonal component using the following code: ser = ts(data, freq=48) dec_1 = stl(ser, s.window="per") Then, I decomposed the irregular component of the decomposed series (dec_1) by setting the frequency to be the second seasonal component, such that: ser2 = ts(dec_1$time.series[,3], freq=336) dec_2 = stl(ser2, s.window="per") I'm not very confident with this approach. And I would like to know if there are any other ways to decompose a series that has multiple seasonalities. Also,I have noticed that the tbats() function in the R forecast<http://cran.r-project.org/web/packages/forecast/index.html> package () allows one to fit a model to a series with multiple seasonalities. Basically, i would like the STL result to be components of Figure 5 on Page 28 of this article (http://robjhyndman.com/papers/complex-seasonality/). However, it doesn't say how to implement (the decomposition in R. Does anyone know how to apply the tbats() function in R for decomposition? Regards [[alternative HTML version deleted]] ______________________________________________ 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.
