public void WilcoxonNullDistribution()
{
// Pick a very non-normal distribution
ContinuousDistribution d = new ExponentialDistribution();
Random rng = new Random(271828);
foreach (int n in TestUtilities.GenerateIntegerValues(4, 64, 4))
{
Sample wSample = new Sample();
ContinuousDistribution wDistribution = null;
for (int i = 0; i < 128; i++)
{
BivariateSample sample = new BivariateSample();
for (int j = 0; j < n; j++)
{
double x = d.GetRandomValue(rng);
double y = d.GetRandomValue(rng);
sample.Add(x, y);
}
TestResult wilcoxon = sample.WilcoxonSignedRankTest();
wSample.Add(wilcoxon.Statistic);
wDistribution = wilcoxon.Distribution;
}
TestResult ks = wSample.KolmogorovSmirnovTest(wDistribution);
Assert.IsTrue(ks.Probability > 0.05);
Assert.IsTrue(wSample.PopulationMean.ConfidenceInterval(0.99).ClosedContains(wDistribution.Mean));
Assert.IsTrue(wSample.PopulationStandardDeviation.ConfidenceInterval(0.99).ClosedContains(wDistribution.StandardDeviation));
}
}
public void WilcoxonNullDistribution()
{
// Pick a very non-normal distribution
ContinuousDistribution d = new ExponentialDistribution();
Random rng = new Random(271828);
foreach (int n in TestUtilities.GenerateIntegerValues(4, 64, 4))
{
Sample wContinuousSample = new Sample();
ContinuousDistribution wContinuousDistribution = null;
List <int> wDiscreteSample = new List <int>();
DiscreteDistribution wDiscreteDistribution = null;
for (int i = 0; i < 256; i++)
{
BivariateSample sample = new BivariateSample();
for (int j = 0; j < n; j++)
{
double x = d.GetRandomValue(rng);
double y = d.GetRandomValue(rng);
sample.Add(x, y);
}
TestResult wilcoxon = sample.WilcoxonSignedRankTest();
if (wilcoxon.UnderlyingStatistic != null)
{
wDiscreteSample.Add(wilcoxon.UnderlyingStatistic.Value);
wDiscreteDistribution = wilcoxon.UnderlyingStatistic.Distribution;
}
else
{
wContinuousSample.Add(wilcoxon.Statistic.Value);
wContinuousDistribution = wilcoxon.Statistic.Distribution;
}
}
if (wDiscreteDistribution != null)
{
TestResult chi2 = wDiscreteSample.ChiSquaredTest(wDiscreteDistribution);
Assert.IsTrue(chi2.Probability > 0.01);
}
else
{
TestResult ks = wContinuousSample.KolmogorovSmirnovTest(wContinuousDistribution);
Assert.IsTrue(ks.Probability > 0.01);
Assert.IsTrue(wContinuousSample.PopulationMean.ConfidenceInterval(0.99).ClosedContains(wContinuousDistribution.Mean));
Assert.IsTrue(wContinuousSample.PopulationStandardDeviation.ConfidenceInterval(0.99).ClosedContains(wContinuousDistribution.StandardDeviation));
}
}
}