[
https://issues.apache.org/jira/browse/STATISTICS-31?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17383309#comment-17383309
]
Benjamin W Trent commented on STATISTICS-31:
--------------------------------------------
[~aherbert]
> did you try pushing the values and the resulting probabilities further out
>into the long tail?
For some of them I did do manual tests in an even longer tail and they passed
fine. I can update the current values to push it out even further if desired.
Having values < 0.1e-16 would require bumping up the absolute tolerance.
[~erans]
> tabulation changes (e.g. in {{BetaDistributionTest}}) that should rather
>belong in a dedicated PR
If I could I would, but I was getting formatting failures in the PR.
> mention of {{// These were created using WolframAlpha}} sometimes comes with
> the query, sometimes not
Very true, I can clean this up, the function name is probably not necessary.
The exception being the Gumbel distribution.
> I wonder why the {{protected}} methods in class
>{{ContinuousDistributionAbstractTest}} aren't annotated with {{@Test}}, rather
>than be called from other methods in the same class.
I was confused by the same thing. But to keep myself from doing tons of
refactoring, I decided to keep the pattern as it is. Seems to me that tons of
this test code can be refactored and made cleaner.
> Add survival probability function to continuous distributions
> -------------------------------------------------------------
>
> Key: STATISTICS-31
> URL: https://issues.apache.org/jira/browse/STATISTICS-31
> Project: Apache Commons Statistics
> Issue Type: New Feature
> Reporter: Benjamin W Trent
> Priority: Major
> Time Spent: 40m
> Remaining Estimate: 0h
>
> It is useful to know the [survival
> function|[https://en.wikipedia.org/wiki/Survival_function]] of a number given
> a continuous distribution.
> While this can be approximated with
> {noformat}
> 1 - cdf(x){noformat}
> , there is an opportunity for greater accuracy in certain distributions.
>
> A good example of this is the gamma distribution. The survival function for
> that distribution would probably look similar to:
>
> ```java
> @Override
> public double survivalProbability(double x) {
> if (x <= SUPPORT_LO)
> { return 1; }
> else if (x >= SUPPORT_HI)
> { return 0; }
> return RegularizedGamma.Q.value(shape, x / scale);
> }
> ```
>
--
This message was sent by Atlassian Jira
(v8.3.4#803005)
