[
https://issues.apache.org/jira/browse/MATH-1153?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14249124#comment-14249124
]
Phil Steitz commented on MATH-1153:
-----------------------------------
Sorry I did not comment on the goodness of fit tests. Those are more
problematic, as having to cherry-pick seeds indicates that the generated values
may not follow the target distribution. Looking at G-tests as well would be a
good idea, as would looking at a range of different distribution parameter
values.
I will have a look at the code and homogeneity tests tonight.
> 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: 3.4
>
> Attachments: 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.
--
This message was sent by Atlassian JIRA
(v6.3.4#6332)
