Peter Bloomfield's Fourier Analysis of Time Series is a good reference for this sort of thing...
On Jan 10, 2008, at 5:25 PM, Gabor Grothendieck wrote: > To do it from first principles using nonlinear optimization see: > http://finzi.psych.upenn.edu/R/Rhelp02a/archive/20100.html > > On Jan 10, 2008 5:27 PM, Carson Farmer <[EMAIL PROTECTED]> wrote: >> Hello R community, >> >> Does anyone know of a package that will perform cycle regression >> analysis? I have searched the R-help archives etc. but have come up >> with >> nothing so far. >> If I am unable to find an existing R package to do so, is there >> anyone >> familiar with fitting sine functions to data. My problem is this: >> I have a long time-series of daily SWE estimates (SWE = snow water >> equivalence, or the amount of water stored in a snowpack) which >> follows >> a sinusoidal pattern, and I need to estimate the parameters of the >> sine >> function that best fits this data. While there may be many >> contributing >> sine functions and/or linear trends, I am only interested in a single >> sine function that most closely fits the data (trends can be removed >> separately if need be). Perhaps some sort of non-linear least >> squares >> method would be best? >> >> Any help, or suggestions to get me on the right track are greatly >> appreciated. >> >> Carson >> >> ______________________________________________ >> 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. >> > > ______________________________________________ > 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. ______________________________________________ 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.
