The 'fda' package supports fitting finite Fourier series with examples in 'canadian-weather.R' and 'gait.R' in the 'demo' subdirectory of '~R\library\fda\fda'; see also 'fda-ch01.R' in the 'scripts' subdirectory. Also, the 'percur' funcction in the 'DierckxSpline' package supports fitting periodic splines.
stephen sefick wrote: > well if you want to find the spectral density aka what frequencies > explain most of the variance then I would suggest the spectral > density. This can be implemented with spec.pgram(). This is > conducted with the fast fourier transform algorithm. > >> a<-ts(data, frequency = 1) #make the time series with 365readings/365days >> ?spec.pgram >> > and you should be able to take it from here > > This will give you the raw periodogram and the dominant frequencies > after you smooth the periodogram. If your intention is to just fit a > curve to your data there are many types of cuve fitting options moving > average etc. > > What are you trying to do find the dominant periodicy? make a > prediction equation? fit a smooth line? or... > > give us some more information and maybe we can help > > > On 1/28/08, Carson Farmer <[EMAIL PROTECTED]> wrote: > >> Rolf Turner wrote: >> >>>> On 26/01/2008, at 10:54 AM, Carson Farmer wrote: >>>> >>>> >>>>> Dear List, >>>>> >>>>> I am attempting to perform a harmonic analysis on a time series of snow >>>>> depth, in which the annual curve is essentially asymmetric (i.e. snow >>>>> accumulates slowly over time, and the subsequent melt occurs relatively >>>>> rapidly). I am trying to fit a curve to the data, however, the actual >>>>> frequency is unknown. >>>>> >>> In general the actual frequency of the curve will indeed be close to >>> 1/(1 year). However, because I intend to perform this analysis on many >>> regions, this will not always be the case. This is perhaps an >>> acceptable assumption however... >>> >>>> Obviously there is something I am not understanding here. >>>> I would have thought that the ``actual frequency'' would >>>> be 1/(1 year) (period = 1 year) --- modulo the fact that >>>> the length of the year is constantly changing a tiny bit. >>>> (But I would've thought that this would have no practical >>>> impact in respect of any observed series.) >>>> >>>> >>> My sampling interval is daily. >>> >>>> What is your sampling interval, BTW? Day? Week? Month? >>>> >>>>> I have been trying to follow the methods in Peter >>>>> Bloomfields text "Fourier Analysis of Time Series", but am having >>>>> trouble implementing this in R. >>>>> >>> Yes it certainly would. >>> >>>> Note that even though the ``actual frequency'' is (???) 1/(1 year), >>>> the representation of the mean function in terms of sinusoids >>>> will involve in theory infinitely many terms/frequencies since >>>> the mean function is clearly (!) not a sinusoid. >>>> >>>> >>>>> Does anyone have any suggestions, or perhaps directions on how this >>>>> might be done properly? Am I using the right methods for fitting an >>>>> asymmetric curve? >>>>> >>> What I am really trying to do is fit a relatively smooth line to my >>> data which will preferentially weight the larger values. This method >>> needs to be able to fit through data gaps however, which is why I was >>> originally looking to fit sinusoids. A jpg of a single year of the >>> data is available here: >>> <http://www.geog.uvic.ca/spar/carson/snowDepth.jpg> to give you an >>> idea of the shape of my curve. >>> Thank you again for your help, >>> >>> Carson >>> >>>> I would have to know more about what you are *really* trying >>>> to do, and what the data are like, before I could make any >>>> useful suggestions. Many modelling issues could come into >>>> play, and many modelling strategies are potentially applicable. >>>> >>>> cheers, >>>> >>>> Rolf Turner >>>> >>>> >> ______________________________________________ >> 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.
