# Re: st: Use of Weights in Kernel Density Estimation

 From Bmilanovic@worldbank.org To statalist@hsphsun2.harvard.edu Subject Re: st: Use of Weights in Kernel Density Estimation Date Sun, 16 Nov 2003 12:38:06 -0500

```      Ramani,

why don;t you multiply the weights by a hundred (or whatever; a thousand),
and then create integers. kdensity should  work then.

best, branko

IMPORTANTISSIMO!!!
From around October 15, 2003 my new
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Ramani Gunatilaka
<Ramani.Gunatilaka@buseco.mon                                          To:
ash.edu.au>                           Statalist@Hsphsun2.Harvard.Edu
Sent by:                             cc:
owner-statalist@hsphsun2.harv        Subject:  st: Use of Weights in Kernel Density Estimation
ard.edu

11/16/2003 09:11 AM
Please respond to statalist

Hi all,
I hope there maybe someone out there who may be able to help me with this query.
I have a household level data set of roughly 19,000 households with the
following variables: per capita consumption in rupees (x), population weights
(w) and household size (hhsize) as in the sample below (I'm sorry the column
heads are not aligned).

x            w           hhsize
204.4059           176.45            3
402.0174           119.22            6
218.7155           51.84             8
1083.199           1266.73           6
303.6877           169.54            3

The weights represent the number of households in the entire population that
each particular household represents.

I need to estimate the kernel density of the consumption distribution and have
consulted Stata's kdensity function as well as the akdensity module developed by
Van Kerm. Both permit the use of weights, but only of fweights and aweights. But
while the weights in my data set are frequency weights, they are certainly not
integers as required by Stata.

Would someone know how I may get round this problem? I'd rather use the kdensity
or akdensity commands and not have to write up a programme from scratch.

Thanks so much,
Ramani
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