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https://issues.apache.org/jira/browse/MATH-753?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=13216529#comment-13216529
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Sébastien Brisard commented on MATH-753:
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This suits me fine. The only concern I have is that using exp(log(x)) in place
of x might incur a loss of accuracy. Maybe we should use this substitution only
when it is necessary (for large values of alpha and beta). This would require a
little bit of investigation to find the appropriate thresholds.
> Better implementation for the gamma distribution density function
> -----------------------------------------------------------------
>
> Key: MATH-753
> URL: https://issues.apache.org/jira/browse/MATH-753
> Project: Commons Math
> Issue Type: Improvement
> Affects Versions: 2.2
> Reporter: Francesco Strino
> Priority: Minor
> Labels: improvement, stability
> Fix For: 2.2
>
>
> The way the density of the gamma distribution function is estimated can be
> improved.
> It's much more stable to calculate first the log of the density and then
> exponentiate, otherwise the function returns NaN for high values of the
> parameters alpha and beta.
> It would be sufficient to change the public double density(double x) function
> at line 204 in the file
> org.apache.commons.math.distribution.GammaDistributionImpl as follows:
> return Math.exp(Math.log( x )*(alpha-1) - Math.log(beta)*alpha - x/beta -
> Gamma.logGamma(alpha));
> In order to improve performance, log(beta) and Gamma.logGamma(alpha) could
> also be precomputed and stored during initialization.
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