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https://issues.apache.org/jira/browse/STATISTICS-31?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17383292#comment-17383292
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Alex Herbert edited comment on STATISTICS-31 at 7/19/21, 12:02 PM:
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I've not looked over the PR in detail but I did notice that the new survival
probability functions are tested with probabilities in the range 1e-7 to 1e-9
or so with a default absolute tolerance of 1e-15. Given the limit of 1 - CDF(
x) is 2^-53 (or approximately 1.11e-16) did you try pushing the values and the
resulting probabilities further out into the long tail?
was (Author: alexherbert):
I've not looked over the PR in detail but I did notice that the new survival
probability functions are tested with probabilities in the range 1e-7 to 1e-9
or so with a default absolute tolerance of 1e-15. Given the limit of 1 - CDF(x)
is 2^-53 (or approximately 1.11e-16) did you try pushing the values and the
resulting probabilities further out into the long tail?
> 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);
> }
> ```
>
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