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From "Phil Steitz (JIRA)" <j...@apache.org>
Subject [jira] Commented: (MATH-385) Characteristic (support, mean, variance, ...) on Distributions
Date Sun, 26 Sep 2010 20:46:33 GMT

    [ https://issues.apache.org/jira/browse/MATH-385?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=12915033#action_12915033
] 

Phil Steitz commented on MATH-385:
----------------------------------

Looks good, modulo one pesky detail that will go away when things become immutable in 3.0:
 you need to modify setters that could change characteristics to set the isCalculated flags
to false.

> Characteristic (support, mean, variance, ...) on Distributions
> --------------------------------------------------------------
>
>                 Key: MATH-385
>                 URL: https://issues.apache.org/jira/browse/MATH-385
>             Project: Commons Math
>          Issue Type: New Feature
>            Reporter: Mikkel Meyer Andersen
>             Fix For: 2.2
>
>         Attachments: MATH385-PATCH1
>
>   Original Estimate: 5h
>  Remaining Estimate: 5h
>
> I wish that the Distributions could contain some characteristics. For example support,
mean, and variance.
> Support:
> AbstractContinuousDistribution and AbstractIntegerDistribution should have double getSupport{Lower,
Upper}Bound() and int getSupport{Lower, Upper}Bound(), respectively. Also methods a la boolean
isSupport{Lower, Upper}BoundInclusive() on AbstractContinuousDistribution should reflect if
the support is open of closed. In practise the implemented distributions are easy since the
support for all continuous distributions are real intervals (connected sets), and the support
for all the discrete distributions are connected integer sets. This means that the lower and
upper bound (together with isSupport{Lower, Upper}BoundInclusive() on AbstractContinuousDistribution
because it is not needed on the discrete distributions because of their nature) are sufficient
for determine the support.
> Mean and variance:
> double get{Mean, Variance}() should be on AbstractDistribution.
> With such characteristic an invalidateParameters-method might come in handy because they
often depend on the parameters. The characteristics should not be calculated before the first
time they are get'ted, and when calculated, they should be saved for later use.  When parameters
change, an invalidateParameters-method should be called to force the characteristics to be
recalculated.
> Values such as Double.POSITIVE_INFINITY, Double.NEGATIVE_INFINITY, and Double.NaN should
be used where appropriate.

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