Dear Dennis, thanks a lot for your response. I have two time series and need to approximate there joint density.
The only thing I cannot find out is how to find the values of this function in the points not from the resulting grid matrix Thanks a lot You're using a function that provides an estimate of a *continuous* > bivariate density > to approximate a bivariate discrete distribution? If your joint > distribution is discrete, there are > better ways to visualize it, and I'll leave it up to you to discover how. > (Hint: look at the 3D > graphics packages.) > > DM > > On Wed, Dec 2, 2009 at 2:14 AM, Trafim <rdapam...@gmail.com> wrote: > >> Dear all, >> >> Please, look at the following code: >> >> attach(geyser) >> f1 <- kde2d(duration, waiting, n = 5) >> >> a <- 0 >> for (i in 1:5){ >> for (j in 1:5){ >> a <- a + f1$z[i,j] >> } >> } >> >> As far as I understood from Help kde2d returns matrix elements of which >> are >> values of joint probability mass function Pr(X=x,Y=y) therefore, sum of >> its >> elements should sum to 1. >> Which is not the case from my check. >> Where is the problem here? >> >> Thanks a lot. >> >> [[alternative HTML version deleted]] >> >> ______________________________________________ >> 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. >> > > [[alternative HTML version deleted]] ______________________________________________ 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.