I have a time series that contains double seasonal components 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 package allows one to fit a model to a series with multiple seasonalities however, it doesn't say how to decompose a series with it.