why not just use the tools in npudens? they can predict on a new set. You can also you tools like fitdistr to fit a parametric multivariate density, or you can use loess or lm with poly or splines to estimate the surface (but this will not guarantee a volume of 1).
On Thu, Jan 15, 2015 at 2:19 AM, rala <stach...@gmx.de> wrote: > Thanks for the reply. I have datapoints. > What I actually want to do is to estimate a joint density function. > I used npudens() to estimate the kernel density of two vectors and got the > densities at the evaluation points. Now I want an approximation for this so > I can have an estimate for different points. > > > > -- > View this message in context: > http://r.789695.n4.nabble.com/Approximation-of-a-function-from-R-2-to-R-tp4701805p4701828.html > Sent from the R help mailing list archive at Nabble.com. > > ______________________________________________ > R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see > 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. > -- Gregory (Greg) L. Snow Ph.D. 538...@gmail.com [[alternative HTML version deleted]] ______________________________________________ R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see 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.