I just realized after some tips and a little digging that what I was trying to do "manually" has already been done. I was trying to fit my data using 'lm' then taking the "residual" data and trying to do a spectral estimate (for seasonality) usiing fft and then passing the "residual" of all of that to arima to get the irregular portion of the time series forecast equation. I found 'stl' that advertises that it does all of this (and probably better than my efforts). The only problem that I found was that it takes a time-series object. Time-series objects don't handle missing observations. Say I only have two observations for the year (enough to fit a line through). I can easily fit a line through the observation points but if I add in zeros for the missing observations least squares will undoubtedly throw my observations out and fit the "wrong" line. The other steps will more than likely have residual data so I don't have to worry for these steps about missing data. Has anyon! e used 'stl' with missing observations? If so what sort of tricks did you use to get around the missing data and time series?
Thank you. Kevin ______________________________________________ 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.
