Mike HC
2009-Jul-08 11:31 UTC
[R] stats::decompose - Problem finding seasonal component without trend
Hi R-help, I'd like to extract the seasonal component of a short timeseries, and was hoping to use stats::decompose. I don't want to decompose the 'trend' component so I thought I should call decompose(x,filter=0). I think I've either misunderstood the filter argument or come upon a bug/feature in decompose. # EXAMPLE x<-ts(c(2:12,rep(1,12),1:12),start=c(2009,2),frequency=12);x # Starts in Feb # Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec #2009 2 3 4 5 6 7 8 9 10 11 12 #2010 1 1 1 1 1 1 1 1 1 1 1 1 #2011 1 2 3 4 5 6 7 8 9 10 11 12 decompose(x) #ok, got some answer for seasonal component, but I don't want to split the residual into trend and random. decompose(x,filter=0) #this seems broken, ignoring some of the data in seasonal calculation, and losing some points in the random component # END EXAMPLE I've debug-stepped through decompose and, as far as I can understand the manipulation, it appears to ignore the first and last period. And only the middle 12 points (all 1 in my example) are used in the calculation of the seasonal averages. Unrelated, but it also seems to duplicate one value during the calculation, and throw a warning due to a seemingly unnecessary 'end' argument to window. I can probably get away with using some function like sweep or scale instead, but please let me know if I'm just misusing decompose. If it's a bug, I hope the above helps.. Regards, Mike P.S. I see this comment in the R 2.8.0 release notes: o HoltWinters() and decompose() use a (statistically) more efficient computation for seasonal fits (they used to waste one period). I'm on R 2.80: _ platform i386-pc-mingw32 arch i386 os mingw32 system i386, mingw32 status major 2 minor 8.0 year 2008 month 10 day 20 svn rev 46754 language R version.string R version 2.8.0 (2008-10-20) -- View this message in context: http://www.nabble.com/stats%3A%3Adecompose----Problem-finding-seasonal-component-without-trend-tp24389771p24389771.html Sent from the R help mailing list archive at Nabble.com.