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);
}
