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https://issues.apache.org/jira/browse/MATH-731?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=13184774#comment-13184774
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Sébastien Brisard commented on MATH-731:
----------------------------------------

Patch committed in {{r1230419}}, with the following changes
* Removed {{getLowerLimit()}} and {{getUpperLimit()}}, which are redundant with 
{{getSupportLowerBound()}} and {{getSupportUpperBound()}} (the Javadoc is 
explicit enough about that).
* Implemented explicit formulas for {{inverseCumulativeProbability(double)}}.
* Removed DEFAULT_INVERSE_ABSOLUTE_ACCURACY, which has now become meaningless 
(since {{inverseCumulativeProbability(double)}} no longer resorts to an 
iterative solver). I guess {{getSolverAbsoluteAccuracy()}} should return a 
reliable estimate on the absolute accuracy of the explicit calculations 
performed in {{inverseCumulativeProbability(double)}}. As I have not a clear 
view on what this accuracy is, I've {color:red}arbitrarily{color} initialized 
{{solverAbsoluteAccuracy}} with {{FastMath.ulp(c)}}. It should probably rather 
be something like {{s * FastMath.ulp(c)}}, with {{s > 1}} depending on {{a}}, 
{{b}} and {{c}}. {color:red}Thoughts?{color}
* Used default implementation of {{sample()}} instead of proposed version, as 
they are *exactly* identical (see explicit implementation of 
{{inverseCumulativeProbability(double)}}.
* Removed references to Ivan Frohnes' code.
* Updated serialVersionUID

I'll leave this issue unresolved until we come to an agreement on the accuracy 
issue.

Thanks for this contribution!

Afterthoughts: we should probably implement explicit expressions as well for 
the inverse cumulative probability of a uniform distribution.
                
> Triangular distribution
> -----------------------
>
>                 Key: MATH-731
>                 URL: https://issues.apache.org/jira/browse/MATH-731
>             Project: Commons Math
>          Issue Type: New Feature
>            Reporter: Dennis Hendriks
>            Assignee: Sébastien Brisard
>              Labels: distribution
>             Fix For: 3.0
>
>         Attachments: triangular_distribution.patch
>
>
> It would be nice to have a triangular distribution.

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