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https://issues.apache.org/jira/browse/MATH-1153?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14522216#comment-14522216
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Thomas Neidhart commented on MATH-1153:
---------------------------------------
Looking at the wikipedia page I found another way to sample from a beta
distribution:
{code}
sample X from a gamma distribution with parameters (alpha, 1)
sample Y from a gamma distribution with parameters (beta, 1)
return X / (X + Y)
{code}
I quickly tested this method and it is even faster than the Cheng method,
succeeding the tests.
The same method is also implemented in mahout (see
https://github.com/apache/mahout/blob/master/mr/src/main/java/org/apache/mahout/clustering/UncommonDistributions.java)
> 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: 4.0
>
> Attachments: ChengBetaSampler.java, ChengBetaSampler.java,
> ChengBetaSamplerTest.java
>
>
> 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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