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https://issues.apache.org/jira/browse/MATH-585?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Mikkel Meyer Andersen updated MATH-585:
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Attachment: MATH585-1.patch
This is _NOT_ a final patch proposal!
This is partly for experimenting and validation purposes (the old inversion
based nextGamma is renamed to nextOldGamma), and partly for showing how I
solved the many constants and caching involved in the algorithms (see the new
class GammaRejectionSampler - I'm not sure what how I myself think about that
way of doing it, maybe a private class in RandomDataImpl is better?).
So please comment on those two subjects.
> 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
> Assignee: Mikkel Meyer Andersen
> Labels: Gamma, Random
> Attachments: MATH585-1.patch
>
> 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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