public void InverseGammaDistributionConstructorTest2()
{
var invGamma = new InverseGammaDistribution(shape: 0.42, scale: 0.5);
double mean = invGamma.Mean; // -0.86206896551724133
double median = invGamma.Median; // 3.1072323347401709
double var = invGamma.Variance; // -0.47035626665061164
double cdf = invGamma.DistributionFunction(x: 0.27); // 0.042243552114989695
double pdf = invGamma.ProbabilityDensityFunction(x: 0.27); // 0.35679850067181362
double lpdf = invGamma.LogProbabilityDensityFunction(x: 0.27); // -1.0305840804381006
double ccdf = invGamma.ComplementaryDistributionFunction(x: 0.27); // 0.95775644788501035
double icdf = invGamma.InverseDistributionFunction(p: cdf); // 0.26999994629410995
double hf = invGamma.HazardFunction(x: 0.27); // 0.3725357333377633
double chf = invGamma.CumulativeHazardFunction(x: 0.27); // 0.043161763098266373
string str = invGamma.ToString(CultureInfo.InvariantCulture); // Γ^(-1)(x; α = 0.42, β = 0.5)
Assert.AreEqual(-0.86206896551724133, mean);
Assert.AreEqual(3.1072323347401709, median, 1e-7);
Assert.AreEqual(-0.47035626665061164, var);
Assert.AreEqual(0.043161763098266373, chf);
Assert.AreEqual(0.042243552114989695, cdf, 1e-10);
Assert.AreEqual(0.35679850067181362, pdf);
Assert.AreEqual(-1.0305840804381006, lpdf);
Assert.AreEqual(0.3725357333377633, hf);
Assert.AreEqual(0.95775644788501035, ccdf);
Assert.AreEqual(0.27, icdf, 1e-8);
Assert.AreEqual("Γ^(-1)(x; α = 0.42, β = 0.5)", str);
double p05 = invGamma.DistributionFunction(median);
Assert.AreEqual(0.5, p05, 1e-6);
}
public void InverseGammaDistributionConstructorTest2()
{
var invGamma = new InverseGammaDistribution(shape: 0.42, scale: 0.5);
double mean = invGamma.Mean; // -0.86206896551724133
double median = invGamma.Median; // 3.1072323347401709
double var = invGamma.Variance; // -0.47035626665061164
double mode = invGamma.Mode; // 0.35211267605633806
double cdf = invGamma.DistributionFunction(x: 0.27); // 0.042243552114989695
double pdf = invGamma.ProbabilityDensityFunction(x: 0.27); // 0.35679850067181362
double lpdf = invGamma.LogProbabilityDensityFunction(x: 0.27); // -1.0305840804381006
double ccdf = invGamma.ComplementaryDistributionFunction(x: 0.27); // 0.95775644788501035
double icdf = invGamma.InverseDistributionFunction(p: cdf); // 0.26999994629410995
double hf = invGamma.HazardFunction(x: 0.27); // 0.3725357333377633
double chf = invGamma.CumulativeHazardFunction(x: 0.27); // 0.043161763098266373
string str = invGamma.ToString(CultureInfo.InvariantCulture); // Γ^(-1)(x; α = 0.42, β = 0.5)
Assert.AreEqual(-0.86206896551724133, mean);
Assert.AreEqual(3.1072323347401709, median, 1e-7);
Assert.AreEqual(-0.47035626665061164, var);
Assert.AreEqual(0.35211267605633806, mode);
Assert.AreEqual(0.043161763098266373, chf);
Assert.AreEqual(0.042243552114989695, cdf, 1e-10);
Assert.AreEqual(0.35679850067181362, pdf);
Assert.AreEqual(-1.0305840804381006, lpdf);
Assert.AreEqual(0.3725357333377633, hf);
Assert.AreEqual(0.95775644788501035, ccdf);
Assert.AreEqual(0.27, icdf, 1e-7);
Assert.AreEqual("Γ^(-1)(x; α = 0.42, β = 0.5)", str);
double p05 = invGamma.DistributionFunction(median);
Assert.AreEqual(0.5, p05, 1e-6);
var range1 = invGamma.GetRange(0.95);
var range2 = invGamma.GetRange(0.99);
var range3 = invGamma.GetRange(0.01);
Assert.AreEqual(0.29141691452733387, range1.Min);
Assert.AreEqual(834.10323133076645, range1.Max);
Assert.AreEqual(0.16305763832571143, range2.Min);
Assert.AreEqual(38513.540845383861, range2.Max);
Assert.AreEqual(0.16305763832571132, range3.Min);
Assert.AreEqual(38513.540845383861, range3.Max);
Assert.AreEqual(4.94065645841247E-324, invGamma.Support.Min);
Assert.AreEqual(double.PositiveInfinity, invGamma.Support.Max);
Assert.AreEqual(invGamma.InverseDistributionFunction(0), invGamma.Support.Min);
Assert.AreEqual(invGamma.InverseDistributionFunction(1), invGamma.Support.Max);
}
public void InverseGammaDistributionConstructorTest()
{
double actual, expected;
{
InverseGammaDistribution target = new InverseGammaDistribution(4, 2);
actual = target.ProbabilityDensityFunction(-2);
expected = 0;
Assert.AreEqual(expected, actual);
actual = target.ProbabilityDensityFunction(5);
expected = 0.000572006;
Assert.AreEqual(expected, actual, 1e-6);
Assert.IsFalse(Double.IsNaN(actual));
actual = target.ProbabilityDensityFunction(0.42);
expected = 1.74443;
Assert.AreEqual(expected, actual, 1e-6);
Assert.IsFalse(Double.IsNaN(actual));
}
{
InverseGammaDistribution target = new InverseGammaDistribution(2.4, 0.42);
actual = target.ProbabilityDensityFunction(0);
expected = 0;
Assert.AreEqual(expected, actual);
Assert.IsFalse(Double.IsNaN(actual));
actual = target.ProbabilityDensityFunction(0.3);
expected = 1.4838600;
Assert.AreEqual(expected, actual, 1e-7);
Assert.IsFalse(Double.IsNaN(actual));
actual = target.ProbabilityDensityFunction(0.42);
expected = 0.705140;
Assert.AreEqual(expected, actual, 1e-6);
Assert.IsFalse(Double.IsNaN(actual));
}
}
public void MedianTest()
{
var target = new InverseGammaDistribution(shape: 4.2, scale: 7.8);
Assert.AreEqual(target.Median, target.InverseDistributionFunction(0.5));
}
