R help - Apr 2012 - STL decomposition of time series with multiple seasonalities

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]]