[
https://issues.apache.org/jira/browse/STATISTICS-31?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17383334#comment-17383334
]
Alex Herbert commented on STATISTICS-31:
----------------------------------------
It is a feature.
I just tried this example:
{code:java}
class BaseTest {
@Test
void test1() {
// Pass
}
@Test
void test2() {
// Pass
}
}
class ChildTest extends BaseTest {
void test1() {
Assertions.fail();
}
}
{code}
If you excute {{ChildTest}} then it does not run test1. It only runs test2.
Inheritence is not the JUnit 5 way. However if you have a lot of boiler plate
code then it is not too bad to put it all in a base class. I'd have to do more
reading on this to see if there is a better way to have the tests for all the
distributions fit the JUnit 5 way.
> 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)
