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
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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/