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Posted to issues@commons.apache.org by "Sergei Lebedev (JIRA)" <ji...@apache.org> on 2014/09/30 17:50:33 UTC

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

Sergei Lebedev created MATH-1153:
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             Summary: 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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