public void ConstructorTest() { var vonMises = new VonMisesDistribution(mean: 0.42, concentration: 1.2); double mean = vonMises.Mean; // 0.42 double median = vonMises.Median; // 0.42 double var = vonMises.Variance; // 0.48721760532782921 double cdf = vonMises.DistributionFunction(x: 1.4); // 0.81326928491589345 double pdf = vonMises.ProbabilityDensityFunction(x: 1.4); // 0.2228112141141676 double lpdf = vonMises.LogProbabilityDensityFunction(x: 1.4); // -1.5014304395467863 double ccdf = vonMises.ComplementaryDistributionFunction(x: 1.4); // 0.18673071508410655 double icdf = vonMises.InverseDistributionFunction(p: cdf); // 1.3999999637927665 double hf = vonMises.HazardFunction(x: 1.4); // 1.1932220899695576 double chf = vonMises.CumulativeHazardFunction(x: 1.4); // 1.6780877262500649 string str = vonMises.ToString(CultureInfo.InvariantCulture); // VonMises(x; μ = 0.42, κ = 1.2) double imedian = vonMises.InverseDistributionFunction(p: 0.5); Assert.AreEqual(0.42, mean); Assert.AreEqual(0.42, median); Assert.AreEqual(0.42000000260613551, imedian, 1e-8); Assert.AreEqual(0.48721760532782921, var); Assert.AreEqual(1.6780877262500649, chf); Assert.AreEqual(0.81326928491589345, cdf); Assert.AreEqual(0.2228112141141676, pdf); Assert.AreEqual(-1.5014304395467863, lpdf); Assert.AreEqual(1.1932220899695576, hf); Assert.AreEqual(0.18673071508410655, ccdf); Assert.AreEqual(1.39999999999, icdf, 1e-8); Assert.AreEqual("VonMises(x; μ = 0.42, κ = 1.2)", str); }
/// <summary> /// Estimates a new von-Mises distribution from a given set of angles. /// </summary> /// public static VonMisesDistribution Estimate(double[] angles, double[] weights, VonMisesOptions options) { VonMisesDistribution vonMises = new VonMisesDistribution(); vonMises.Fit(angles, weights, options); return(vonMises); }
public void ConstructorTest1() { // If p=2 the distribution reduces to the von Mises distribution on the circle. double kappa = 4.2; var vm = new VonMisesDistribution(0, kappa); var target = new VonMisesFisherDistribution(new double[] { -1, 0 }, kappa); double s = Math.Sqrt(2) / 2; double[] mean = target.Mean; double a000 = target.ProbabilityDensityFunction(new double[] { +1, +0 }); double a045 = target.ProbabilityDensityFunction(new double[] { +s, +s }); double a090 = target.ProbabilityDensityFunction(new double[] { +0, +1 }); double a135 = target.ProbabilityDensityFunction(new double[] { -s, +s }); double a180 = target.ProbabilityDensityFunction(new double[] { -1, +0 }); double a225 = target.ProbabilityDensityFunction(new double[] { -s, -s }); double a270 = target.ProbabilityDensityFunction(new double[] { +0, -1 }); double a315 = target.ProbabilityDensityFunction(new double[] { +s, -s }); double a360 = target.ProbabilityDensityFunction(new double[] { +1, +0 }); double offset = -Math.PI; double e000 = vm.ProbabilityDensityFunction(offset + 0); double e045 = vm.ProbabilityDensityFunction(offset + Math.PI / 4); double e090 = vm.ProbabilityDensityFunction(offset + Math.PI / 2); double e135 = vm.ProbabilityDensityFunction(offset + Math.PI * (3 / 4.0)); double e180 = vm.ProbabilityDensityFunction(offset + Math.PI); double e225 = vm.ProbabilityDensityFunction(offset + Math.PI * (5 / 4.0)); double e270 = vm.ProbabilityDensityFunction(offset + Math.PI * (3 / 2.0)); double e315 = vm.ProbabilityDensityFunction(offset + Math.PI * (7 / 4.0)); double e360 = vm.ProbabilityDensityFunction(offset + Math.PI * 2); Assert.AreEqual(e000, a000, 1e-8); Assert.AreEqual(e045, a045, 1e-8); Assert.AreEqual(e090, a090, 1e-8); Assert.AreEqual(e135, a135, 1e-8); Assert.AreEqual(e180, a180, 1e-8); Assert.AreEqual(e225, a225, 1e-8); Assert.AreEqual(e270, a270, 1e-8); Assert.AreEqual(e315, a315, 1e-8); Assert.AreEqual(e360, a360, 1e-8); }
public void MedianTest() { VonMisesDistribution target = new VonMisesDistribution(1.621, 4.52); Assert.AreEqual(target.Median, target.InverseDistributionFunction(0.5), 1e-6); }
public void LogProbabilityDensityFunctionTest() { VonMisesDistribution dist = new VonMisesDistribution(2.249981, 2.411822); double x = 2.14; double actual = dist.LogProbabilityDensityFunction(x); double expected = System.Math.Log(dist.ProbabilityDensityFunction(x)); Assert.AreEqual(expected, actual, 1e-10); }
public void ProbabilityDensityFunctionTest() { VonMisesDistribution dist = new VonMisesDistribution(2.249981, 2.411822); double actual = dist.ProbabilityDensityFunction(2.14); double expected = 0.5686769438969197; Assert.AreEqual(expected, actual, 1e-10); }
public void ConstructorTest17() { var original = new VonMisesDistribution(mean: 0.42, concentration: 1.2); var vonMises = GeneralContinuousDistribution.FromDistributionFunction( original.Support, original.DistributionFunction); for (double i = -10; i < +10; i += 0.1) { double expected = original.ProbabilityDensityFunction(i); double actual = vonMises.ProbabilityDensityFunction(i); Assert.IsTrue(expected.IsRelativelyEqual(actual, 1e-4)); } testVonMises(vonMises, 1); }
public void ConstructorTest16() { var original = new VonMisesDistribution(mean: 0.42, concentration: 1.2); var vonMises = GeneralContinuousDistribution.FromDensityFunction( original.Support, original.ProbabilityDensityFunction); testVonMises(vonMises, 100); }
public void ConstructorTest17() { var original = new VonMisesDistribution(mean: 0.42, concentration: 1.2); var vonMises = GeneralContinuousDistribution.FromDistributionFunction( original.Support, original.DistributionFunction); testVonMises(vonMises); }
/// <summary> /// Estimates a new von-Mises distribution from a given set of angles. /// </summary> /// public static VonMisesDistribution Estimate(double[] angles, double[] weights, VonMisesOptions options) { VonMisesDistribution vonMises = new VonMisesDistribution(); vonMises.Fit(angles, weights, options); return vonMises; }