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 /
*
* For searches and help try:
* http://www.stata.com/support/faqs/res/findit.html
* http://www.stata.com/support/statalist/faq
* http://www.ats.ucla.edu/stat/stata/
