public void WaldFit()
{
WaldDistribution wald = new WaldDistribution(3.5, 2.5);
FrameTable results = new FrameTable();
results.AddColumns <double>("Mean", "Shape", "MeanVariance", "ShapeVariance", "MeanShapeCovariance");
for (int i = 0; i < 128; i++)
{
Sample sample = SampleTest.CreateSample(wald, 16, i);
WaldFitResult result = WaldDistribution.FitToSample(sample);
Assert.IsTrue(result.Mean.Value == result.Parameters.ValuesVector[result.Parameters.IndexOf("Mean")]);
Assert.IsTrue(result.Shape.Value == result.Parameters.ValuesVector[result.Parameters.IndexOf("Shape")]);
Assert.IsTrue(TestUtilities.IsNearlyEqual(result.Parameters.VarianceOf("Mean"), MoreMath.Sqr(result.Mean.Uncertainty)));
Assert.IsTrue(TestUtilities.IsNearlyEqual(result.Parameters.VarianceOf("Shape"), MoreMath.Sqr(result.Shape.Uncertainty)));
results.AddRow(
result.Mean.Value, result.Shape.Value,
result.Parameters.VarianceOf("Mean"), result.Parameters.VarianceOf("Shape"), result.Parameters.CovarianceOf("Mean", "Shape")
);
}
Assert.IsTrue(results["Mean"].As <double>().PopulationMean().ConfidenceInterval(0.99).ClosedContains(wald.Mean));
Assert.IsTrue(results["Shape"].As <double>().PopulationMean().ConfidenceInterval(0.99).ClosedContains(wald.Shape));
Assert.IsTrue(results["Mean"].As <double>().PopulationVariance().ConfidenceInterval(0.99).ClosedContains(results["MeanVariance"].As <double>().Median()));
Assert.IsTrue(results["Shape"].As <double>().PopulationVariance().ConfidenceInterval(0.99).ClosedContains(results["ShapeVariance"].As <double>().Median()));
Assert.IsTrue(results["Mean"].As <double>().PopulationCovariance(results["Shape"].As <double>()).ConfidenceInterval(0.99).ClosedContains(results["MeanShapeCovariance"].As <double>().Median()));
}
public void WaldFit()
{
WaldDistribution wald = new WaldDistribution(3.5, 2.5);
BivariateSample parameters = new BivariateSample();
MultivariateSample variances = new MultivariateSample(3);
for (int i = 0; i < 128; i++)
{
Sample s = SampleTest.CreateSample(wald, 16, i);
FitResult r = WaldDistribution.FitToSample(s);
parameters.Add(r.Parameters[0], r.Parameters[1]);
variances.Add(r.Covariance(0, 0), r.Covariance(1, 1), r.Covariance(0, 1));
Assert.IsTrue(r.GoodnessOfFit.Probability > 0.01);
}
Assert.IsTrue(parameters.X.PopulationMean.ConfidenceInterval(0.99).ClosedContains(wald.Mean));
Assert.IsTrue(parameters.Y.PopulationMean.ConfidenceInterval(0.99).ClosedContains(wald.Shape));
Assert.IsTrue(parameters.X.PopulationVariance.ConfidenceInterval(0.99).ClosedContains(variances.Column(0).Median));
Assert.IsTrue(parameters.Y.PopulationVariance.ConfidenceInterval(0.99).ClosedContains(variances.Column(1).Median));
Assert.IsTrue(parameters.PopulationCovariance.ConfidenceInterval(0.99).ClosedContains(variances.Column(2).Median));
}