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Re: st: how to simulate an arbitrary distribution


From   "Joseph Coveney" <jcoveney@bigplanet.com>
To   "Statalist" <statalist@hsphsun2.harvard.edu>
Subject   Re: st: how to simulate an arbitrary distribution
Date   Fri, 4 Apr 2008 22:38:06 +0900

Jeph Herrin wrote:

This must have been addressed here before, but I can't
find it.

I have a dataset of 1500 observations, each with an
identifier and a -y- value. -y- is highly skewed, and
nothing I've tried seems to normalize it.

I'd like to simulate the distribution of -y-. Is there
a reasonable way to do this if I can't find a transform
of it that looks like a standard distribution?

--------------------------------------------------------------------------------

Take a look at -jnsn- and -jnsw- for getting estimates of the parameters
that characterize y's distribution, and then feed these values into -ajv- to
stimulate y's distribution.

All three are bundled in the same package on SSC (-findit jnsn-).

Joseph Coveney


jnsn from http://fmwww.bc.edu/RePEc/bocode/j
 'JNSN': module to fit Johnson distributions / jnsn comprises four commands
 that collectively fit parameters of / Johnson distributions by two methods
 (moment matching and / quantiles), transform a variable into a quasinormal
 deviate / after fitting Johnson distribution parameter estimates, and /


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