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Date: Tue, 2 Sep 2008 01:18:44 -0700 (PDT)
From: "Ted Dunning (JIRA)" <jira@apache.org>
To: issues@commons.apache.org
Subject: [jira] Updated: (MATH-222) Need way to compute density of
 distributions
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     [ https://issues.apache.org/jira/browse/MATH-222?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Ted Dunning updated MATH-222:
-----------------------------

    Attachment: MATH-222-with-beta.patch

This is a patch that implements the proposed density computation and adds an implementation of the beta distribution.

I know that the addition of the beta distribution is a bit out of scope, but I was going to add that in any case and it would have needed a density method so it would have depended on this patch.  To avoid dependencies, I merged the changes.

A version of this patch without the beta distribution is also attached to this issue.  If the other patch is put into trunk, I will be happy to submit a separate patch for the beta distribution.

> Need way to compute density of distributions
> --------------------------------------------
>
>                 Key: MATH-222
>                 URL: https://issues.apache.org/jira/browse/MATH-222
>             Project: Commons Math
>          Issue Type: New Feature
>            Reporter: Ted Dunning
>         Attachments: MATH-222-with-beta.patch, MATH-222.patch
>
>
> Currently, there are a number of distributions defined in commons math, but the interface for Distribution and ContinuousDistribution doesn't provide for the computation of the PDF at a particular point.
> It is common for it to be necessary to compute the density function, for example in the Metropolis algorithm.
> It is also pretty common for it to be very difficult to compute a density function or for the density function to be undefined as certain points.  Only the cumulative density is mathematically assured.
> Thus, I propose to create a new interface HasDensityFunction<T> that requires the implementation of a double density(T) method.  T is the type of the argument for the density function which would be Double in the case of most univariate statistics, but could, for instance, be a vector of doubles for a Dirichlet distribution or a vector of integers for a Multinomial.

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