R help - Apr 2006 - bivariate weighted kernel density estimator

Is there code for bivariate kernel density estimation?
For bivariate kernels there is
kde2d in MASS
kde2d.g in GRASS
KernSur in GenKern
(list probably incomplete)
but none of them seems to accept a weight parameter
(like density does since R 2.2.0)

-- 
Erich Neuwirth, University of Vienna
Faculty of Computer Science
Computer Supported Didactics Working Group
Visit our SunSITE at http://sunsite.univie.ac.at
Phone: +43-1-4277-39464 Fax: +43-1-4277-39459

Erich Neuwirth writes:
> Is there code for bivariate kernel density estimation?
> ...
> but none of them seems to accept a weight parameter
In package 'spatstat' the function density.ppp performs weighted kernel
smoothing,
including bivariate kernel density estimation.

At the moment it only offers the Gaussian kernel
but we plan to include other kernels.

Adrian Baddeley

On Sun, 23 Apr 2006 09:13:35 +0200, Erich Neuwirth wrote:

EN> Is there code for bivariate kernel density estimation?
EN> For bivariate kernels there is
EN> kde2d in MASS
EN> kde2d.g in GRASS
EN> KernSur in GenKern
EN> (list probably incomplete)
EN> but none of them seems to accept a weight parameter
EN> (like density does since R 2.2.0)
EN> 

sm.density of package sm allows to use weights 
(with Gaussian kernel)

best wishes,
Adelchi Azzalini

-- 
Adelchi Azzalini  <azzalini at stat.unipd.it>
Dipart.Scienze Statistiche, Universit? di Padova, Italia
tel. +39 049 8274147,  http://azzalini.stat.unipd.it/

Dear Roger,
thanks for the suggestion.
That is the solution, just modifying kde2d.
I did it slightly differently.
Since I have up to 200000 points,
diag(Z) from your code becomes too large.
But since t(matrix(dnorm(ay),n,nx)) only needs to be
multiplied with the weights rowwise and
* applied to vectors repeats the shorter vector cyclically,
Z * t(matrix(dnorm(ay)))
does the same thing as
diag(Z) %*% t(matrix(dnorm(ay),n,nx))

and does not need too much memory.

I also have to add an excuse:
In the original posting I stated that I need WEIGHTED kernel
density estimators in the subject,
but did not mention weighted in the text.
That was imprecise and probably therefore I mislead some list
participants.

Erich


Roger Bivand wrote:
> kde2d.G is just kde2d with two changes - it takes the grid from the GRASS
> region, and it allows weights in the Z argument. Please have a look at
the
> code and see if you can't simply retro-fit it to kde2d:
>
>     if (!is.null(Z)) {
>         if (length(Z) != nx)
>             stop("Data vectors must be the same length")
>         z1 <- matrix(dnorm(ax), n, nx) %*% diag(Z) %*%
t(matrix(dnorm(ay),
>             n, nx))/(nx * h[1] * h[2])
>         z <- z1/z
>     }
>
> This was put into the function to make a very crude kernel density
> interpolator with the grid cell values scaled in the units of the Z
> variable.
>
-- 
Erich Neuwirth, University of Vienna
Faculty of Computer Science
Computer Supported Didactics Working Group
Visit our SunSITE at http://sunsite.univie.ac.at
Phone: +43-1-4277-39464 Fax: +43-1-4277-39459