What a simple and brilliant idea!
Thanks Branko, I really appreciate that!
Ramani
[email protected] wrote:
> 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
> Email address will be
> [email protected]
>
>
> ALL ABOUT INEQUALITY IN THE WORLD (AND MORE!)
> http://www.worldbank.org/research/inequality/
>
>
>
>
>
> Ramani Gunatilaka
> <[email protected] To:
> ash.edu.au> [email protected]
> Sent by: cc:
> [email protected] 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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