public void Constructor_ExtensiveTestForDocumentation() { // Create a new Kumaraswamy distribution with shape (4,2) var kumaraswamy = new KumaraswamyDistribution(a: 4, b: 2); double mean = kumaraswamy.Mean; // 0.71111111111111114 double median = kumaraswamy.Median; // 0.73566031573423674 double mode = kumaraswamy.Mode; // 0.80910671157022118 double var = kumaraswamy.Variance; // 0.027654320987654302 double cdf = kumaraswamy.DistributionFunction(x: 0.4); // 0.050544639999999919 double pdf = kumaraswamy.ProbabilityDensityFunction(x: 0.4); // 0.49889280000000014 double lpdf = kumaraswamy.LogProbabilityDensityFunction(x: 0.4); // -0.69536403596913343 double ccdf = kumaraswamy.ComplementaryDistributionFunction(x: 0.4); // 0.94945536000000008 double icdf = kumaraswamy.InverseDistributionFunction(p: cdf); // 0.40000011480618253 double hf = kumaraswamy.HazardFunction(x: 0.4); // 0.52545155993431869 double chf = kumaraswamy.CumulativeHazardFunction(x: 0.4); // 0.051866764053008864 string str = kumaraswamy.ToString(CultureInfo.InvariantCulture); // Kumaraswamy(x; a = 4, b = 2) Assert.AreEqual(0.71111111111111114, mean); Assert.AreEqual(0.73566031573423674, median); Assert.AreEqual(0.80910671157022118, mode); Assert.AreEqual(0.027654320987654302, var); Assert.AreEqual(0.051866764053008864, chf); Assert.AreEqual(0.050544639999999919, cdf); Assert.AreEqual(0.49889280000000014, pdf); Assert.AreEqual(-0.69536403596913343, lpdf); Assert.AreEqual(0.52545155993431869, hf); Assert.AreEqual(0.94945536000000008, ccdf); Assert.AreEqual(0.40000011480618253, icdf); Assert.AreEqual("Kumaraswamy(x; a = 4, b = 2)", str); var range1 = kumaraswamy.GetRange(0.95); var range2 = kumaraswamy.GetRange(0.99); var range3 = kumaraswamy.GetRange(0.01); Assert.AreEqual(0.39890408640473385, range1.Min); Assert.AreEqual(0.93868623055832956, range1.Max); Assert.AreEqual(0.26608174016394209, range2.Min); Assert.AreEqual(0.97400390609144138, range2.Max); Assert.AreEqual(0.26608174016394187, range3.Min); Assert.AreEqual(0.97400390609144138, range3.Max); }