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new 4774ada Changed samplers parametric test failure probability.
4774ada is described below
commit 4774ada3ec6eb0fb21455f3975fc5df1d697cbc9
Author: aherbert <[email protected]>
AuthorDate: Thu Sep 26 17:00:09 2019 +0100
Changed samplers parametric test failure probability.
Only 1 re-run is allowed and the number of samplers is high enough that
spurious failures are realistic for the samplers.
Changed the Continuous samplers failure rate from p=0.0138 to p=0.0016.
This is an effective change of numFailures(n=50, p=0.01) > 2 to
numFailures(n=50, p=0.01) > 3.
Changed the Discrete samplers failure rate from p=0.0000189 to p=0.0016
to match the continuous samplers test. Each test is now assessed at the
p=0.01 level not the p=0.001 level. This is an effective change of
numFailures(n=50, p=0.001) > 2 to numFailures(n=50, p=0.01) > 3.
---
.../distribution/ContinuousSamplerParametricTest.java | 10 +++++++++-
.../sampling/distribution/DiscreteSamplerParametricTest.java | 12 ++++++++++--
2 files changed, 19 insertions(+), 3 deletions(-)
diff --git
a/commons-rng-sampling/src/test/java/org/apache/commons/rng/sampling/distribution/ContinuousSamplerParametricTest.java
b/commons-rng-sampling/src/test/java/org/apache/commons/rng/sampling/distribution/ContinuousSamplerParametricTest.java
index e6bfa81..199e504 100644
---
a/commons-rng-sampling/src/test/java/org/apache/commons/rng/sampling/distribution/ContinuousSamplerParametricTest.java
+++
b/commons-rng-sampling/src/test/java/org/apache/commons/rng/sampling/distribution/ContinuousSamplerParametricTest.java
@@ -120,7 +120,15 @@ public class ContinuousSamplerParametricTest {
throw new RuntimeException("Unexpected", e);
}
- if ((double) numFailures / (double) numTests > 0.05) {
+ // The expected number of failed tests can be modelled as a Binomial
distribution
+ // B(n, p) with n=50, p=0.01 (50 tests with a 1% significance level).
+ // The cumulative probability of the number of failed tests (X) is:
+ // x P(X>x)
+ // 1 0.0894
+ // 2 0.0138
+ // 3 0.0016
+
+ if (numFailures > 3) { // Test will fail with 0.16% probability
Assert.fail(sampler + ": Too many failures for sample size = " +
sampleSize +
" (" + numFailures + " out of " + numTests + " tests
failed, " +
"chi2=" + Arrays.toString(failedStat.toArray(new
Double[0])) + ")");
diff --git
a/commons-rng-sampling/src/test/java/org/apache/commons/rng/sampling/distribution/DiscreteSamplerParametricTest.java
b/commons-rng-sampling/src/test/java/org/apache/commons/rng/sampling/distribution/DiscreteSamplerParametricTest.java
index 1c947e7..379c914 100644
---
a/commons-rng-sampling/src/test/java/org/apache/commons/rng/sampling/distribution/DiscreteSamplerParametricTest.java
+++
b/commons-rng-sampling/src/test/java/org/apache/commons/rng/sampling/distribution/DiscreteSamplerParametricTest.java
@@ -106,7 +106,7 @@ public class DiscreteSamplerParametricTest {
}
}
- if (chiSquareTest.chiSquareTest(expected, observed, 0.001)) {
+ if (chiSquareTest.chiSquareTest(expected, observed, 0.01)) {
failedStat.add(chiSquareTest.chiSquareTest(expected,
observed));
++numFailures;
}
@@ -116,7 +116,15 @@ public class DiscreteSamplerParametricTest {
throw new RuntimeException("Unexpected", e);
}
- if ((double) numFailures / (double) numTests > 0.05) {
+ // The expected number of failed tests can be modelled as a Binomial
distribution
+ // B(n, p) with n=50, p=0.01 (50 tests with a 1% significance level).
+ // The cumulative probability of the number of failed tests (X) is:
+ // x P(X>x)
+ // 1 0.0894
+ // 2 0.0138
+ // 3 0.0016
+
+ if (numFailures > 3) { // Test will fail with 0.16% probability
Assert.fail(sampler + ": Too many failures for sample size = " +
sampleSize +
" (" + numFailures + " out of " + numTests + " tests
failed, " +
"chi2=" + Arrays.toString(failedStat.toArray(new
Double[0])));
