R help - Nov 2008 - 2D density tophat

Hello R users,
I have successfully created a square (or more generally, rectangular) tophat
smoothing routine based on altering the already available KDE2D. I would be
keen to implement a circular tophat routine also, however this appears to be
much more difficult to write efficiently (I have a routine, but it's very
slow). I tried to create one based on using crossdist to create a distance
matrix between my data and the sampling grid, but it doesn't take a
particularly large amount of data (or hi res grid) for memory to be a big
problem. The 2D density routines I have been able to find either don't
support a simple tophat, or don't use the absolute distances between the
sampling grid and the data. Should anyone know of more general 2D density
routines that might support circular tophats, or know of a simple and
efficient method for creating them, I would be very grateful.

Aaron

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Hello R users,

I have successfully created a square (or more generally, rectangular)  
tophat smoothing routine based on altering the already available  
KDE2D. I would be keen to implement a circular tophat routine also,  
however this appears to be much more difficult to write efficiently (I  
have a routine, but it's very slow). I tried to create one based on  
using crossdist (in spatstat) to create a distance matrix between my  
data and the sampling grid, but it doesn't take a particularly large  
amount of data (or hi-res grid) for memory to be a big problem. The 2D  
density routines I have been able to find either don't support a  
simple tophat, or don't use the absolute distances between the  
sampling grid and the data. Should anyone know of more general 2D  
density routines that might support circular tophats, or know of a  
simple and efficient method for creating them, I would be very grateful.

Thanks for your time,

Aaron

PS: I tried sending this on Friday originally, but as far as I know  
that didn't work, so should another post appear from me asking the  
same thing I apologise in advance.
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