I have a set of data that is basically 3+ years of data. It is daily sales for this year and then back 3 years so there are 3*365 + 231 days or 1326 days of data. Since this is a time series I have constructed it as:
Start = c(1, 1) End = c(4, 231) Frequency = 365 In trying to ayalyze this data I first turned to stl to break the time series into components. This worked really well but I would like to be able to forecast and my attempts so far at applying ARIMA to the "remainder" portion of the stl output have failed. So I decided to try a different approach. I decided to let arima handle the seasonal part as well. So I tried: tarima = arima(TimeSeries, order=c(1,1,1), seasonal=list(order=c(1,1,1))) But this call results in the error: Error in makeARIMA(trarma[[1]], trarma[[2]], Delta, kappa) : maximum supported lag is 350 Is it not possible to use ARIMA to fiit daily seasonsal data as I have described? Am I missing something fundamental? 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.
