[jira] [Commented] (MATH-1153) Sampling from a 'BetaDistribution' is slow

["Thomas Neidhart (JIRA)" <ji...@apache.org>]

    [ https://issues.apache.org/jira/browse/MATH-1153?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14153620#comment-14153620 ] 

Thomas Neidhart commented on MATH-1153:
---------------------------------------

Hi Sergei,

yes, please attach the patch so we can evaluate it, the performance improvements are really significant.

> Sampling from a 'BetaDistribution' is slow
> ------------------------------------------
>
>                 Key: MATH-1153
>                 URL: https://issues.apache.org/jira/browse/MATH-1153
>             Project: Commons Math
>          Issue Type: Improvement
>            Reporter: Sergei Lebedev
>            Priority: Minor
>             Fix For: 3.3
>
>
> Currently the `BetaDistribution#sample` uses inverse CDF method, which is quite slow for sampling-intensive computations. I've implemented a method from the R. C. H. Cheng paper and it seems to work much better. Here's a simple microbenchmark:
> {code}
> o.j.b.s.SamplingBenchmark.algorithmBCorBB       1e-3    1000  thrpt        5  2592200.015    14391.520  ops/s
> o.j.b.s.SamplingBenchmark.algorithmBCorBB       1000    1000  thrpt        5  3210800.292    33330.791  ops/s
> o.j.b.s.SamplingBenchmark.commonsVersion        1e-3    1000  thrpt        5    31034.225      438.273  ops/s
> o.j.b.s.SamplingBenchmark.commonsVersion        1000    1000  thrpt        5    21834.010      433.324  ops/s
> {code}
> Should I submit a patch?
> R. C. H. Cheng (1978). Generating beta variates with nonintegral shape parameters. Communications of the ACM, 21, 317–322.



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