Frequency too high for ets?
Thank you. I did get a valiuable technique for debugging that I didn't know before from your comments. So from your comments I gather the limit for exponential smoothing is 24. Not having much experience with exponential smoothing is it unreasonable to expect an algorithm to handle frequencies > 24? I started out with daily data (365 observations per year). I quickly realized that there were not any available fitting algorithms that could handle that degree of resolution. I tried splitting the year in half and splitting the year into quarters (91 observations per quarter). I finally found that if I have 52 observations per year I can use arima to fit and ARIMA model to my data. That seemed like a compromise that I could live with but it was still a compromise. Now if I want to fit an exponential smoothing model I need to further reduce the frequency by more than a half. Are there other packages that can handle this? I would like to be able to forecast down to any given week in the year if possible. In other words if I feed in something like week 48 I would like to be able to handle this. Reommendations? Thank you. Kevin
---- Josh Ulrich <josh.m.ulrich at gmail.com> wrote:
Look at the source:
x <- ts(rnorm(52*100),frequency=52) debug(ets) e <- ets(x)
<snip>
debug: m <- frequency(y)
Browse[1]>
debug: if (m > 24) stop("Frequency too high")
Browse[1]>
Error in ets(x) : Frequency too high
--
http://quantemplation.blogspot.com
On Mon, Sep 22, 2008 at 12:15 PM, <rkevinburton at charter.net> wrote:
I have a time series that is basically weekly data for a year. So the frequency on the time-series is 52 (52 weeks (obeservations)/year). I have 3+ years of data. I am trying to fit a model to this data using ets in the forecast package (exponential smoothing) but I get: Error in ets(.sublist$TimeSeries) : Frequency too high I was looking in the documentation for 'ets' and there was no mention of the limits but apparently 52 is "too high". Any suggestions? Thank you. Kevin
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