public void ValidateProbability(double[] p, int[] x, double res) { var b = new Multinomial(p, x.Sum()); AssertHelpers.AlmostEqual(b.Probability(x), res, 12); }
public void CanComputeNormInfinity() { var vector = CreateVector(Data); AssertHelpers.AlmostEqual(5.0990195, vector.Norm(Single.PositiveInfinity).Real, 7); }
public void ValidateCumulativeDistribution(double location, double scale, double dof, double x, double c) { var n = new StudentT(location, scale, dof); AssertHelpers.AlmostEqual(c, n.CumulativeDistribution(x), 13); }
public void CanComputeNorm() { var vector = CreateVector(Data); AssertHelpers.AlmostEqual(7.7459666f, vector.Norm(2).Real, 7); }
public void CanComputeSquareNorm() { var vector = CreateVector(Data); AssertHelpers.AlmostEqual(60f, vector.Norm(2).Real *vector.Norm(2).Real, 6); }
public void ValidateEntropy([Values(0.0, 0.3, 1.0)] double p, [Values(4, 3, 2)] int n, [Values(0.0, 1.1404671643037712668976423399228972051669206536461, 0.0)] double e) { var b = new Binomial(p, n); AssertHelpers.AlmostEqual(e, b.Entropy, 14); }
public void ValidateDensityLn(double[] x) { var d = new Dirichlet(new[] { 0.1, 0.3, 0.5, 0.8 }); AssertHelpers.AlmostEqual(d.DensityLn(x), Math.Log(d.Density(x)), 12); }
public void ValidateDensityLn(double shape, double scale, double x, double pdfln) { var n = new Weibull(shape, scale); AssertHelpers.AlmostEqual(pdfln, n.DensityLn(x), 14); }
public void ValidateCumulativeDistribution(double shape, double scale, double x, double cdf) { var n = new Weibull(shape, scale); AssertHelpers.AlmostEqual(cdf, n.CumulativeDistribution(x), 15); }
public void ValidateSkewness(double shape, double scale, double skewness) { var n = new Weibull(shape, scale); AssertHelpers.AlmostEqual(skewness, n.Skewness, 11); }
public void ValidateMedian(double shape, double scale, double median) { var n = new Weibull(shape, scale); AssertHelpers.AlmostEqual(median, n.Median, 13); }
public void ValidateStdDev(double shape, double scale, double sdev) { var n = new Weibull(shape, scale); AssertHelpers.AlmostEqual(sdev, n.StdDev, 13); }
public void ValidateVariance(double shape, double scale, double var) { var n = new Weibull(shape, scale); AssertHelpers.AlmostEqual(var, n.Variance, 13); }
public void ValidateProbabilityLn(int[] x) { var b = new Multinomial(largeP, x.Sum()); AssertHelpers.AlmostEqual(b.ProbabilityLn(x), Math.Log(b.Probability(x)), 12); }
public void CanComputeNormInfinity() { var vector = CreateVector(Data); AssertHelpers.AlmostEqual(5.09901951359279, vector.Norm(Double.PositiveInfinity), 15); }
public void ValidateProbabilityLn([Values(new[] { 1, 2, 3, 4, 5, 6, 7, 8, 9 }, new[] { 1, 1, 1, 2, 2, 2, 3, 3, 3 }, new[] { 5, 6, 7, 8, 7, 6, 5, 4, 3 })] int[] x) { var b = new Multinomial(_largeP, x.Sum()); AssertHelpers.AlmostEqual(b.ProbabilityLn(x), Math.Log(b.Probability(x)), 12); }
public void ValidateSkewness(double scale, double skn) { var n = new Rayleigh(scale); AssertHelpers.AlmostEqual(skn, n.Skewness, 17); }
public void ValidateCumulativeDistribution(double x, double f) { var n = Normal.WithMeanStdDev(5.0, 2.0); AssertHelpers.AlmostEqual(f, n.CumulativeDistribution(x), 10); }
public void ValidateDensity(double[] x, double res) { var d = new Dirichlet(new[] { 0.1, 0.3, 0.5, 0.8 }); AssertHelpers.AlmostEqual(res, d.Density(x), 12); }
public void ValidateInverseCumulativeDistribution(double x, double f) { var n = Normal.WithMeanStdDev(5.0, 2.0); AssertHelpers.AlmostEqual(x, n.InverseCumulativeDistribution(f), 15); }
public void ValidateCumulativeDistribution(int size, int m, int n, double x, double cdf) { var d = new Hypergeometric(size, m, n); AssertHelpers.AlmostEqual(cdf, d.CumulativeDistribution(x), 14); }
public void CanComputeNorm() { var vector = CreateVector(Data); AssertHelpers.AlmostEqual(7.74596669241483, vector.Norm(2), 15); }
public void CanComputeNorm1() { var vector = CreateVector(Data); AssertHelpers.AlmostEqual(16.0346843f, vector.Norm(1).Real, 7); }
public void CanComputeNorm1() { var vector = CreateVector(Data); AssertHelpers.AlmostEqual(16.0346843392517, vector.Norm(1), 15); }
public void CanComputeNormP([Values(1, 2, 3, 10)] int p, [Values(16.0346843392517f, 7.74596669241483f, 6.28528392332871f, 5.1608912235454f)] float expected) { var vector = CreateVector(Data); AssertHelpers.AlmostEqual(expected, vector.Norm(p).Real, 5); }
public void CanComputeSquareNorm() { var vector = CreateVector(Data); AssertHelpers.AlmostEqual(60.0, vector.Norm(2) * vector.Norm(2), 15); }
public void ValidateDensityLn(double location, double scale, double dof, double x, double p) { var n = new StudentT(location, scale, dof); AssertHelpers.AlmostEqual(p, n.DensityLn(x), 13); }
public void CanComputeNormP([Values(1, 2, 3, 10)] int p, [Values(16.0346843392517, 7.74596669241483, 6.28528392332871, 5.1608912235454)] double expected) { var vector = CreateVector(Data); AssertHelpers.AlmostEqual(expected, vector.Norm(p), 15); }
public void NullableMean([Values("lottery", "lew", "mavro", "michelso", "numacc1", "numacc2", "numacc3", "numacc4")] string dataSet) { var data = _data[dataSet]; AssertHelpers.AlmostEqual(data.Mean, data.DataWithNulls.Mean(), 15); }
public void NullableStandardDeviationConsistentWithNistData(string dataSet, int digits) { var data = _data[dataSet]; AssertHelpers.AlmostEqual(data.StandardDeviation, Statistics.StandardDeviation(data.DataWithNulls), digits); }