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https://issues.apache.org/jira/browse/RNG-149?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17373527#comment-17373527
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Alex Herbert commented on RNG-149:
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I have created a version based on the ZigguratNormalizedGaussianSampler.
I added this to the JMH examples and ran using:
{noformat}
mvn package -Pexamples-jmh
java -jar target/examples-jmh.jar \
ContinuousSamplersPerformance -p \
samplerType=AhrensDieterExponentialSampler,ZigguratExponentialSampler \
-p randomSourceName=XO_RO_SHI_RO_128_PP
{noformat}
The speed of the Ziggurat sampler is much faster (4x) than the current
AhrensDieterExponentialSampler:
||Sampler||Score||Error||
|Baseline|2.434|0.060|
|AhrensDieterExponentialSampler|24.788|0.329|
|ZigguratExponentialSampler|7.450|0.101|
> ZigguratExponentialSampler
> --------------------------
>
> Key: RNG-149
> URL: https://issues.apache.org/jira/browse/RNG-149
> Project: Commons RNG
> Issue Type: New Feature
> Components: sampling
> Affects Versions: 1.4
> Reporter: Alex Herbert
> Priority: Major
>
> The paper describing the ZigguratNormalizedGaussianSampler also provides code
> for sampling from an exponential distribution.
> {code:java}
> public class ZigguratExponentialSampler implements
> SharedStateContinuousSampler {
> public ZigguratExponentialSampler
> withUniformRandomProvider(UniformRandomProvider rng);
> public static ZigguratExponentialSampler of(UniformRandomProvider rng);
> public static ZigguratExponentialSampler of(UniformRandomProvider rng,
> double mean);
> }
> {code}
> I suggest allowing creation of a sampler with mean 1. This special case has
> application in other samplers, for example the LargeMeanPoissonSampler.
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