david.meyer at wu-wien.ac.at
2008-May-17 14:10 UTC
[Rd] HoltWinters fitted level parameter not bounded between 0 (PR#11478)
An update on this: I just patched HoltWinters() to use optimize() in the univariate case, and it now computes the correct value. David John Bodley wrote:> Hi, > > Thanks for the quick response. I upgraded by version of R on Windows to the > latest (2.7.0) and re-ran the analysis and get the same result of 48.87989. > > The original time series was a non-regular zoo() object and I converted it > to a time series with daily granularity by setting the values of the > undefined dates to zero. I initially wondered if the zeros were maybe an > issue, i.e., I know multiplicative Holt-Winters requires non-negative > values, so I tried shifting the values, which should change the level, > though the fitted alpha values should be the same: > >> delta <- 10 ^ seq(-3, 0); >> sapply(delta, function(delta) HoltWinters(x + delta, beta = 0, gamma > 0)$alpha); > alpha alpha alpha alpha > 48.8798912 48.8798912 48.8798912 0.6881547 > > Note that by applying a shift, I also obtained varying values of alpha, > similar to that of what David achieved by changing the initial conditions. > > Thanks > -John > > On Fri, May 16, 2008 at 4:20 AM, David Meyer <david.meyer at wu-wien.ac.at> > wrote: > >> I get John's value (48.8789) in 2.7.0 and R-devel (both on Ubuntu). Really >> seems to be a numeric issue: >> >>> HoltWinters(x, beta = 0, gamma = 0)$alpha >> alpha >> 48.87989 >> >>> HoltWinters(x * 1.0000000001, beta = 0, gamma = 0)$alpha >> alpha >> 0.6881547 >> >>> HoltWinters(x * 1.00000000001, beta = 0, gamma = 0)$alpha >> alpha >> 48.87989 >> >> Providing starting values seems to help, but not always: >> >>> HoltWinters(x, beta = 0, gamma = 0, l.start = 0.00001)$alpha >> alpha >> 48.88999 >>> HoltWinters(x, beta = 0, gamma = 0, l.start = 0.0001)$alpha >> alpha >> 0.6880582 >> >> Yes, it's easy to use optimize() instead of optim() in the univariate >> cases, will do. >> >> David. >> >> >> Prof Brian Ripley wrote: >> >>> It doesn't do it on my system (I get a value of about 0.688 in R 2.7.0 >>> patched on Linux), and 2.5.1 is not current. Does a better starting value >>> help? >>> >>> However, HoltWinters is using optim() in a case it is not designed for >>> (one-dimensional optimization): see the note on its help page. I think this >>> could easily be changed, but as HoltWinters is contributed code I am Cc:ing >>> the author for comment. >>> >>> On Fri, 16 May 2008, john.bodley at gmail.com wrote: >>> >>> Full_Name: John Bodley >>>> Version: 2.5.1 (2007-06-27) >>>> OS: Windows XP >>>> Submission from: (NULL) (12.144.182.66) >>>> >>>> >>>> I was fitting a number of time series in R using the stats::HoltWinters >>>> method >>>> to define a single exponential smoothing model, i.e., beta = gamma = 0. >>>> >>>> I came across an example where the fitted value of alpha was not defined >>>> in the >>>> [0, 1] interval which seems to violate the lower and upper bound >>>> constraints >>>> used for the optim method. On my computer the following code returns a >>>> value of >>>> 48.87989. >>>> >>>> R code: >>>> >>>> x <- c( >>>> 0, >>>> 0.000843170320404722, >>>> 0, >>>> 0, >>>> 0, >>>> 0.0103773584905660, >>>> 0.00832466181061394, >>>> 0.0038560411311054, >>>> 0, >>>> 0, >>>> 0.00484966052376334, >>>> 0, >>>> 0, >>>> 0, >>>> 0.00274348422496571, >>>> 0, >>>> 0, >>>> 0, >>>> 0, >>>> 0, >>>> 0.0207064555420219, >>>> 0.0334975369458128, >>>> 0.0334975369458128, >>>> 0.00338983050847458, >>>> 0.00483675937122128, >>>> 0, >>>> 0, >>>> 0.00224971878515186, >>>> 0, >>>> 0, >>>> 0, >>>> 0.00135685210312076, >>>> 0, >>>> 0, >>>> 0, >>>> 0.0035377358490566, >>>> 0.0035377358490566, >>>> 0.00501002004008016, >>>> 0.0107632093933464, >>>> 0, >>>> 0, >>>> 0.0143329658213892, >>>> 0.0330459770114943, >>>> 0, >>>> 0, >>>> 0, >>>> 0, >>>> 0.0109890109890110, >>>> 0, >>>> 0.00118623962040332, >>>> 0.007380073800738, >>>> 0.00695410292072323, >>>> 0.0104895104895105, >>>> 0.00278551532033426, >>>> 0.00278551532033426 >>>> ); >>>> >>>> # Single exponential smoothing >>>> m <- stats::HoltWinters(x, beta = 0, gamma = 0); >>>> m$alpha >>>> >>>> ______________________________________________ >>>> R-devel at r-project.org mailing list >>>> https://stat.ethz.ch/mailman/listinfo/r-devel >>>> >>>> >> -- >> Dr. David Meyer >> Department of Information Systems and Operations >> >> Vienna University of Economics and Business Administration >> Augasse 2-6, A-1090 Wien, Austria, Europe >> Tel: +43-1-313 36 4393 >> Fax: +43-1-313 36 90 4393 >> HP: http://wi.wu-wien.ac.at/~meyer/ <http://wi.wu-wien.ac.at/%7Emeyer/> >> >-- Dr. David Meyer Department of Information Systems and Operations Vienna University of Economics and Business Administration Augasse 2-6, A-1090 Wien, Austria, Europe Tel: +43-1-313 36 4393 Fax: +43-1-313 36 90 4393 HP: http://wi.wu-wien.ac.at/~meyer/
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