public LogProbabilityDensityFunction ( double x ) : double | ||
x | double | A single point in the distribution range. |
Résultat | double |
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); }