[R] kernel smoothing of weighted data

[Prof Brian Ripley]

density() in the R-devel version of R allows weights.

locfit() in the package of the same name also appears to be documented to.

On Tue, 16 Aug 2005 riap2 at cam.ac.uk wrote:

> I want to use kde() or a similar function for kernel smoothing but I want
> to specify the weight of each of my data points.  I do not want to specify
> the bandwidth on a point by point basis.

The only kde() I found is from the recent package ks, and is for 
multivariate data -- if you want that, you did not say so and I've not 
looked for an answer there.

> This seems such a simple and obvious thing to want to do I am suspicious
> that there is not an obvious way to do it.  The only discussion I have
> found is about negative weights(!) and says nothing about implementation.
> Can anyone suggest a package I have missed or suggest the best starting
> point for writing my own solution.
>
> The reason for wanting this is that I have a number of samples each of
> ~1000 data points from the same distribution but the samples are of
> slightly differing statistical weight and eventually each point in each
> sample may have its own statistical weight.
>
> I have searched the list but I am not subscribed to it so please make me an
> addressee of any reply.


-- 
Brian D. Ripley,                  ripley at stats.ox.ac.uk
Professor of Applied Statistics,  http://www.stats.ox.ac.uk/~ripley/
University of Oxford,             Tel:  +44 1865 272861 (self)
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