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st: Kernel density estimation in a large dataset


From   "Eva Poen" <eva.poen@unisg.ch>
To   <statalist@hsphsun2.harvard.edu>
Subject   st: Kernel density estimation in a large dataset
Date   Tue, 16 Nov 2004 16:55:02 +0100

Dear all,

I want to do Kernel density estimation and local polynomial regression
on a dataset with 20'000 observations using Stata 8.2. Computations
using all
observations as a grid, like in

- kdensity x, at(x) gen(xdens) -

take quite a long time (between 10 and 15 minutes each). So I would like
to use a grid of, say, 1000 points, but still have density estimates for
all my observations. That is, I want to have a variable xdens which
contains in observation i

- the exact estimated density if x[i] happens to be a grid point
- the linear interpolation of the two densities estimated at the the
closest grid points to the left and right of x[i]

for all 20'000 observations. I was told that this is the default
behaviour in EViews, but I have really no clue how to best implement
this in Stata.

Thanks a lot for any suggestions.
Best regards,

Eva Poen

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