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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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