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);
}
public void Constructor_KumaraswamyDistribution_PDF_given_0d2_AND_1d2_Parameters_Moments_matches_R_output()
{
var kumaraswamyDistribution = new KumaraswamyDistribution(0.2d, 1.2d);
double mean = kumaraswamyDistribution.Mean; //0.1258821823337952
double variance = kumaraswamyDistribution.Variance; //0.045500725605275683
double median = kumaraswamyDistribution.Median; //0.016262209853672775
double mode = kumaraswamyDistribution.Mode; //NaN
double pdf = kumaraswamyDistribution.ProbabilityDensityFunction(0.3); //0.46195081771596241
double cdf = kumaraswamyDistribution.CumulativeHazardFunction(0.3); //1.8501524192880519
string tostr = kumaraswamyDistribution.ToString(CultureInfo.InvariantCulture); // Kumaraswamy(x; a = 0.2, b = 1.2)
Assert.AreEqual(tostr, "Kumaraswamy(x; a = 0.2, b = 1.2)");
Assert.AreEqual(mean, 0.1258821823337952);
Assert.AreEqual(variance, 0.045500725605275683);
Assert.AreEqual(median, 0.016262209853672775);
Assert.AreEqual(mode, double.NaN);
Assert.AreEqual(pdf, 0.46195081771596241);
Assert.AreEqual(cdf, 1.8501524192880519);
// values verified in R package = ActuDistns
}