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https://issues.apache.org/jira/browse/MATH-585?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=13045326#comment-13045326
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Mikkel Meyer Andersen commented on MATH-585:
--------------------------------------------
I know that it is indeed important, and I will look into it as soon as time
allows me to. R is GPL, so using their implementation is a no-go. But the help
file provides the methods they have implemented:
{quote}
‘rgamma’ for ‘shape >= 1’ uses
Ahrens, J. H. and Dieter, U. (1982). Generating gamma variates by
a modified rejection technique. _Communications of the ACM_,
*25*, 47-54,
and for ‘0 < shape < 1’ uses
Ahrens, J. H. and Dieter, U. (1974). Computer methods for
sampling from gamma, beta, Poisson and binomial distributions.
_Computing_, *12*, 223-246.
{quote}
Again, thanks for reporting this - we'll do our best to improve our
implementation.
> Very slow generation of gamma random variates
> ---------------------------------------------
>
> Key: MATH-585
> URL: https://issues.apache.org/jira/browse/MATH-585
> Project: Commons Math
> Issue Type: Improvement
> Affects Versions: 2.2, 3.0
> Environment: All
> Reporter: Darren Wilkinson
> Labels: Gamma, Random
> Original Estimate: 6h
> Remaining Estimate: 6h
>
> The current implementation of gamma random variate generation works, but uses
> an inversion method. This is well-known to be a bad idea. Usually a carefully
> constructed rejection procedure is used. To give an idea of the magnitude of
> the problem, the Gamma variate generation in Parallel COLT is roughly 50
> times faster than in Commons Math.
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