[R] bivariate kernel density estimates at point locations ( r ather than at grid locations)
andy_liaw at merck.com
Thu Dec 15 21:52:25 CET 2005
You can try `locfit', though it does local likelihood, rather than
garden-variety kernel density estimation. Here's an example:
den.fit <- locfit(~ x1 + x2, data=cltrain)
From: Strickland, Matthew
> My data consists of a set of point locations (x,y).
> I would like to know if there is a procedure for bivariate kernel
> density estimation in R that returns the density estimates at the
> observed point locations rather than at grid locations. I
> have looked at
> a number of different routines and they all seem to return
> estimates at
> grid locations.
> Any type of kernel is fine (i.e., Gaussian, Quartic, etc).
> Thank you for your help!
> Matt Strickland
> U.S. Centers for Disease Control and Prevention
> R-help at stat.math.ethz.ch mailing list
> PLEASE do read the posting guide!
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