Much hinges on whether your i.e. should really be e.g.
But with regard to the distributions mentioned, three
comments:
1. Beta is usually defined for bounded intervals and gamma
and Weibull for half the real line. In broad
terms, if beta is a candidate for your data, then gamma
or Weibull will not be, and vice versa.
2. Fitting programs and quantile-quantile plots for
beta, gamma, and Weibull have been available on SSC
for some years, as -findit- will indicate.
Here are pertinent packages that I know about
on SSC, acknowledging the work of Maarten Buis
and Stephen Jenkins. I mention a few other distributions,
and the list is certainly not complete.
betafit beta distribution
pbeta
qbeta
dirifit Dirichlet distribution
pexp exponential distribution
qexp
gammafit gamma distribution
pgamma
qgamma
gumbelfit Gumbel distribution
pgumbel
qgumbel
pweibull Weibull distribution
qweibull
3. Another approach is density probability plotting
as discussed in
SJ-5-2 gr0012 . . . . . . . . . . Speaking Stata: Density probability plots
Q2/05 SJ 5(2):259--273
discusses use of density probability plots for determining
the density function of a continuous variable, given a data
sample; compares density probability plots with histograms,
kernel density estimation, and quantile--quantile plots
-dpplot- is on SSC.
Nick
[email protected]
Arantxa Roca-Feltrer
> I am trying to check which distribution (i.e. gamma, Weibull, beta)
> better fits my data, but not sure how to do it in Stata. Is there a
> quick (graphical?) way of fitting any of these distributions to my
> data???
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