Frequency too high for ets?
This problem is just a limitation of representing your data as a ts object, not a problem with any exponential smoothing algorithm. The ts class in R is severely limited in the types of regularly spaced time series data that can be represented (annual, quaterly or monthly). A simple fix is to redefine your weekly time series so that it has a frequency of 1 instead of 52; that is, disregard the fact that you have weekly data and just treat each week as one observation. -----Original Message----- From: r-sig-finance-bounces at stat.math.ethz.ch [mailto:r-sig-finance-bounces at stat.math.ethz.ch] On Behalf Of rkevinburton at charter.net Sent: Monday, September 22, 2008 11:38 AM To: Josh Ulrich Cc: r-sig-finance at stat.math.ethz.ch Subject: Re: [R-SIG-Finance] 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
_______________________________________________ R-SIG-Finance at stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-sig-finance -- Subscriber-posting only. -- If you want to post, subscribe first.
_______________________________________________ R-SIG-Finance at stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-sig-finance -- Subscriber-posting only. -- If you want to post, subscribe first.