public void DistributionFunctionTest2()
{
// Verified against http://stattrek.com/online-calculator/hypergeometric.aspx
int population = 20;
int populationSuccess = 8;
int sample = 6;
double[] pmf = { 0.0238390092879257, 0.163467492260062, 0.357585139318886, 0.317853457172343, 0.119195046439628, 0.0173374613003096, 0.000722394220846233 };
double[] less = { 0.0000000000000000, 0.023839009287926, 0.187306501547988, 0.544891640866874, 0.862745098039217, 0.981940144478844, 0.999277605779154 };
double[] lessEqual = { 0.0238390092879257, 0.187306501547988, 0.544891640866874, 0.862745098039217, 0.981940144478845, 0.999277605779154, 1 };
double[] greater = { 0.976160990712074, 0.812693498452012, 0.455108359133126, 0.137254901960783, 0.018059855521155, 0.000722394220845968, 0 };
double[] greaterEqual = { 1, 0.976160990712074, 0.812693498452012, 0.455108359133126, 0.137254901960783, 0.0180598555211555, 0.00072239422084619 };
var target = new HypergeometricDistribution(population, populationSuccess, sample);
for (int i = 0; i < pmf.Length; i++)
{
{ // P(X = i)
double actual = target.ProbabilityMassFunction(i);
Assert.AreEqual(pmf[i], actual, 1e-4);
Assert.IsFalse(Double.IsNaN(actual));
}
{ // P(X <= i)
double actual = target.DistributionFunction(i);
Assert.AreEqual(lessEqual[i], actual, 1e-4);
Assert.IsFalse(Double.IsNaN(actual));
}
{ // P(X < i)
double actual = target.DistributionFunction(i, inclusive: false);
Assert.AreEqual(less[i], actual, 1e-4);
Assert.IsFalse(Double.IsNaN(actual));
}
{ // P(X > i)
double actual = target.ComplementaryDistributionFunction(i);
Assert.AreEqual(greater[i], actual, 1e-4);
Assert.IsFalse(Double.IsNaN(actual));
}
{ // P(X >= i)
double actual = target.ComplementaryDistributionFunction(i, inclusive: true);
Assert.AreEqual(greaterEqual[i], actual, 1e-4);
Assert.IsFalse(Double.IsNaN(actual));
}
}
}
public void ConstructorTest()
{
int populationSize = 15; // population size N
int success = 7; // number of successes in the sample
int samples = 8; // number of samples drawn from N
// Create a new Hypergeometric distribution with N = 15, n = 8, and s = 7
var dist = new HypergeometricDistribution(populationSize, success, samples);
double mean = dist.Mean; // 1.3809523809523812
double median = dist.Median; // 4.0
double var = dist.Variance; // 3.2879818594104315
double mode = dist.Mode; // 4.0
double cdf = dist.DistributionFunction(k: 2); // 0.80488799999999994
double ccdf = dist.ComplementaryDistributionFunction(k: 2); // 0.19511200000000006
double pdf1 = dist.ProbabilityMassFunction(k: 4); // 0.38073038073038074
double pdf2 = dist.ProbabilityMassFunction(k: 5); // 0.18275058275058276
double pdf3 = dist.ProbabilityMassFunction(k: 6); // 0.030458430458430458
double lpdf = dist.LogProbabilityMassFunction(k: 2); // -2.3927801721315989
int icdf1 = dist.InverseDistributionFunction(p: 0.17); // 4
int icdf2 = dist.InverseDistributionFunction(p: 0.46); // 4
int icdf3 = dist.InverseDistributionFunction(p: 0.87); // 5
int icdf4 = dist.InverseDistributionFunction(p: 0.50);
double hf = dist.HazardFunction(x: 4); // 1.7753623188405792
double chf = dist.CumulativeHazardFunction(x: 4); // 1.5396683418789763
string str = dist.ToString(CultureInfo.InvariantCulture); // "HyperGeometric(x; N = 15, m = 7, n = 8)"
Assert.AreEqual(3.7333333333333334, mean);
Assert.AreEqual(4.0, median);
Assert.AreEqual(0.99555555555555553, var);
Assert.AreEqual(4, mode);
Assert.AreEqual(1.5396683418789763, chf, 1e-10);
Assert.AreEqual(0.10023310023310024, cdf);
Assert.AreEqual(0.38073038073038074, pdf1);
Assert.AreEqual(0.18275058275058276, pdf2);
Assert.AreEqual(0.030458430458430458, pdf3);
Assert.AreEqual(-2.3927801721315989, lpdf);
Assert.AreEqual(1.7753623188405792, hf);
Assert.AreEqual(0.89976689976689972, ccdf);
Assert.AreEqual(3, icdf1);
Assert.AreEqual(4, icdf2);
Assert.AreEqual(5, icdf3);
Assert.AreEqual("HyperGeometric(x; N = 15, m = 7, n = 8)", str);
}
public void ConstructorTest()
{
int populationSize = 15; // population size N
int success = 7; // number of successes in the sample
int samples = 8; // number of samples drawn from N
// Create a new Hypergeometric distribution with N = 15, n = 8, and s = 7
var dist = new HypergeometricDistribution(populationSize, success, samples);
double mean = dist.Mean; // 1.3809523809523812
double median = dist.Median; // 4.0
double var = dist.Variance; // 3.2879818594104315
double mode = dist.Mode; // 4.0
double cdf = dist.DistributionFunction(k: 2); // 0.80488799999999994
double ccdf = dist.ComplementaryDistributionFunction(k: 2); // 0.19511200000000006
double pdf1 = dist.ProbabilityMassFunction(k: 4); // 0.38073038073038074
double pdf2 = dist.ProbabilityMassFunction(k: 5); // 0.18275058275058276
double pdf3 = dist.ProbabilityMassFunction(k: 6); // 0.030458430458430458
double lpdf = dist.LogProbabilityMassFunction(k: 2); // -2.3927801721315989
int icdf1 = dist.InverseDistributionFunction(p: 0.17); // 4
int icdf2 = dist.InverseDistributionFunction(p: 0.46); // 4
int icdf3 = dist.InverseDistributionFunction(p: 0.87); // 5
int icdf4 = dist.InverseDistributionFunction(p: 0.50);
double hf = dist.HazardFunction(x: 4); // 1.7753623188405792
double chf = dist.CumulativeHazardFunction(x: 4); // 1.5396683418789763
string str = dist.ToString(CultureInfo.InvariantCulture); // "HyperGeometric(x; N = 15, m = 7, n = 8)"
Assert.AreEqual(3.7333333333333334, mean);
Assert.AreEqual(4.0, median);
Assert.AreEqual(0.99555555555555553, var);
Assert.AreEqual(4, mode);
Assert.AreEqual(1.5396683418789763, chf, 1e-10);
Assert.AreEqual(0.10023310023310024, cdf);
Assert.AreEqual(0.38073038073038074, pdf1);
Assert.AreEqual(0.18275058275058276, pdf2);
Assert.AreEqual(0.030458430458430458, pdf3);
Assert.AreEqual(-2.3927801721315989, lpdf);
Assert.AreEqual(1.7753623188405792, hf);
Assert.AreEqual(0.89976689976689972, ccdf);
Assert.AreEqual(3, icdf1);
Assert.AreEqual(4, icdf2);
Assert.AreEqual(5, icdf3);
Assert.AreEqual("HyperGeometric(x; N = 15, m = 7, n = 8)", str);
}
public void DistributionFunctionTest2()
{
// Verified against http://stattrek.com/online-calculator/hypergeometric.aspx
int population = 20;
int populationSuccess = 8;
int sample = 6;
double[] pmf = { 0.0238390092879257, 0.163467492260062, 0.357585139318886, 0.317853457172343, 0.119195046439628, 0.0173374613003096, 0.000722394220846233 };
double[] less = { 0.0000000000000000, 0.023839009287926, 0.187306501547988, 0.544891640866874, 0.862745098039217, 0.981940144478844, 0.999277605779154 };
double[] lessEqual = { 0.0238390092879257, 0.187306501547988, 0.544891640866874, 0.862745098039217, 0.981940144478845, 0.999277605779154, 1 };
double[] greater = { 0.976160990712074, 0.812693498452012, 0.455108359133126, 0.137254901960783, 0.018059855521155, 0.000722394220845968, 0 };
double[] greaterEqual = { 1, 0.976160990712074, 0.812693498452012, 0.455108359133126, 0.137254901960783, 0.0180598555211555, 0.00072239422084619 };
var target = new HypergeometricDistribution(population, populationSuccess, sample);
for (int i = 0; i < pmf.Length; i++)
{
{ // P(X = i)
double actual = target.ProbabilityMassFunction(i);
Assert.AreEqual(pmf[i], actual, 1e-4);
Assert.IsFalse(Double.IsNaN(actual));
}
{ // P(X <= i)
double actual = target.DistributionFunction(i);
Assert.AreEqual(lessEqual[i], actual, 1e-4);
Assert.IsFalse(Double.IsNaN(actual));
}
{ // P(X < i)
double actual = target.DistributionFunction(i, inclusive: false);
Assert.AreEqual(less[i], actual, 1e-4);
Assert.IsFalse(Double.IsNaN(actual));
}
{ // P(X > i)
double actual = target.ComplementaryDistributionFunction(i);
Assert.AreEqual(greater[i], actual, 1e-4);
Assert.IsFalse(Double.IsNaN(actual));
}
{ // P(X >= i)
double actual = target.ComplementaryDistributionFunction(i, inclusive: true);
Assert.AreEqual(greaterEqual[i], actual, 1e-4);
Assert.IsFalse(Double.IsNaN(actual));
}
}
}