[MATH-1153] Sampling from a 'BetaDistribution' is slow

• Type: Improvement
• Status: Closed
• Priority: Minor
• Resolution: Fixed
• Fix Version/s: 4.0, 3.6
• Assignee: Unassigned
• Reporter: Sergei Lebedev
• Created: 30/Sep/14 15:49
• Updated: 25/Jan/16 20:27
• Resolved: 01/May/15 10:08

Description

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:

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

Should I submit a patch?

R. C. H. Cheng (1978). Generating beta variates with nonintegral shape parameters. Communications of the ACM, 21, 317–322.