I don't have much experience in the subject but it seems that library(akima) should be useful for your problem. Try library(help="akima") to see a list of the functions available in the library.
I hope this helps Francisco >From: Gabor Grothendieck <[EMAIL PROTECTED]> >Reply-To: [EMAIL PROTECTED] >To: David James <[EMAIL PROTECTED]> >CC: r-help@stat.math.ethz.ch >Subject: Re: [R] Interpolating / smoothing missing time series data >Date: Wed, 7 Sep 2005 22:19:17 -0400 > >On 9/7/05, David James <[EMAIL PROTECTED]> wrote: > > The purpose of this email is to ask for pre-built procedures or > > techniques for smoothing and interpolating missing time series data. > > > > I've made some headway on my problem in my spare time. I started > > with an irregular time series with lots of missing data. It even had > > duplicated data. Thanks to zoo, I've cleaned that up -- now I have a > > regular time series with lots of NA's. > > > > I want to use a regression model (i.e. ARIMA) to ill in the gaps. I > > am certainly open to other suggestions, especially if they are easy > > to implement. > > > > My specific questions: > > 1. Presumably, once I get ARIMA working, I still have the problem of > > predicting the past missing values -- I've only seen examples of > > predicting into the future. > > 2. When predicting the past (backcasting), I also want to take > > reasonable steps to make the data look smooth. > > > > I guess I'm looking for a really good example in a textbook or white > > paper (or just an R guru with some experience in this area) that can > > offer some guidance. > > > > Venables and Ripley was a great start (Modern Applied Statistics with > > S). I really had hoped that the "Seasonal ARIMA Models" section on > > page 405 would help. It was helpful, but only to a point. I have a > > hunch (based on me crashing arima numerous times -- maybe I'm just > > new to this and doing things that are unreasonable?) that using > > hourly data just does not mesh well with the seasonal arima code? > >Not sure if this answers your question but if you are looking for something >simple then na.approx in the zoo package will linearly interpolate for you. > > > z <- zoo(c(1,2,NA,4,5)) > > na.approx(z) >1 2 3 4 5 >1 2 3 4 5 > >______________________________________________ >R-help@stat.math.ethz.ch mailing list >https://stat.ethz.ch/mailman/listinfo/r-help >PLEASE do read the posting guide! >http://www.R-project.org/posting-guide.html ______________________________________________ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html