public void NegativeBinomialConstructorTest()
{
double expected, actual;
{
NegativeBinomialDistribution target = new NegativeBinomialDistribution(6, 0.42);
actual = target.ProbabilityMassFunction(-1);
expected = 0.0;
Assert.AreEqual(expected, actual, 1e-7);
Assert.IsFalse(Double.IsNaN(actual));
actual = target.ProbabilityMassFunction(0);
expected = 0.00548903;
Assert.AreEqual(expected, actual, 1e-7);
Assert.IsFalse(Double.IsNaN(actual));
actual = target.ProbabilityMassFunction(1);
expected = 0.0191018;
Assert.AreEqual(expected, actual, 1e-7);
Assert.IsFalse(Double.IsNaN(actual));
actual = target.ProbabilityMassFunction(2);
expected = 0.0387767;
Assert.AreEqual(expected, actual, 1e-7);
Assert.IsFalse(Double.IsNaN(actual));
actual = target.ProbabilityMassFunction(10);
expected = 0.0710119;
Assert.AreEqual(expected, actual, 1e-7);
Assert.IsFalse(Double.IsNaN(actual));
}
}
public void ConstructorTest()
{
// Create a Negative Binomial distribution with r = 7, p = 0.42
var dist = new NegativeBinomialDistribution(failures: 7, probability: 0.42);
// Common measures
double mean = dist.Mean; // 5.068965517241379
double median = dist.Median; // 5.0
double var = dist.Variance; // 8.7395957193816862
// Cumulative distribution functions
double cdf = dist.DistributionFunction(k: 2); // 0.19605133020527743
double ccdf = dist.ComplementaryDistributionFunction(k: 2); // 0.80394866979472257
// Probability mass functions
double pmf1 = dist.ProbabilityMassFunction(k: 4); // 0.054786846293416853
double pmf2 = dist.ProbabilityMassFunction(k: 5); // 0.069908015870399909
double pmf3 = dist.ProbabilityMassFunction(k: 6); // 0.0810932984096639
double lpmf = dist.LogProbabilityMassFunction(k: 2); // -2.3927801721315989
// Quantile function
int icdf1 = dist.InverseDistributionFunction(p: 0.17); // 2
int icdf2 = dist.InverseDistributionFunction(p: 0.46); // 4
int icdf3 = dist.InverseDistributionFunction(p: 0.87); // 8
// Hazard (failure rate) functions
double hf = dist.HazardFunction(x: 4); // 0.10490438293398294
double chf = dist.CumulativeHazardFunction(x: 4); // 0.64959916255036043
// String representation
string str = dist.ToString(CultureInfo.InvariantCulture); // "NegativeBinomial(x; r = 7, p = 0.42)"
Assert.AreEqual(5.068965517241379, mean);
Assert.AreEqual(5.0, median);
Assert.AreEqual(8.7395957193816862, var);
Assert.AreEqual(0.64959916255036043, chf, 1e-10);
Assert.AreEqual(0.19605133020527743, cdf);
Assert.AreEqual(0.054786846293416853, pmf1);
Assert.AreEqual(0.069908015870399909, pmf2);
Assert.AreEqual(0.0810932984096639, pmf3);
Assert.AreEqual(-3.8297538146412009, lpmf);
Assert.AreEqual(0.10490438293398294, hf);
Assert.AreEqual(0.80394866979472257, ccdf);
Assert.AreEqual(2, icdf1);
Assert.AreEqual(4, icdf2);
Assert.AreEqual(8, icdf3);
Assert.AreEqual("NegativeBinomial(x; r = 7, p = 0.42)", str);
var range1 = dist.GetRange(0.95);
var range2 = dist.GetRange(0.99);
var range3 = dist.GetRange(0.01);
Assert.AreEqual(1, range1.Min);
Assert.AreEqual(11.0, range1.Max);
Assert.AreEqual(0, range2.Min);
Assert.AreEqual(14, range2.Max);
Assert.AreEqual(0, range3.Min);
Assert.AreEqual(14, range3.Max);
}
public void pdf()
{
NegativeBinomialDistribution dist = UnivariateDistributionInfo.CreateInstance <NegativeBinomialDistribution>();
Assert.AreEqual(0.5, dist.ProbabilityOfSuccess);
Assert.AreEqual(1, dist.NumberOfFailures);
double median = dist.Median;
Assert.AreEqual(0, median);
int middle = (int)median;
double pdf = dist.ProbabilityMassFunction(middle);
double lpdf = dist.LogProbabilityMassFunction(middle);
Assert.AreEqual(Math.Log(pdf), lpdf, 1e-10);
Assert.AreEqual(pdf, Math.Exp(lpdf), 1e-10);
}
public void ConstructorTest()
{
#region doc_example
// Create a Negative Binomial distribution with r = 7, p = 0.42
var dist = new NegativeBinomialDistribution(failures: 7, probability: 0.42);
// Common measures
double mean = dist.Mean; // 5.068965517241379
double median = dist.Median; // 9.0
double var = dist.Variance; // 8.7395957193816862
// Cumulative distribution functions
double cdf = dist.DistributionFunction(k: 2); // 0.033380251139644379
double ccdf = dist.ComplementaryDistributionFunction(k: 2); // 0.96661974886035562
// Probability mass functions
double pmf1 = dist.ProbabilityMassFunction(k: 4); // 0.054786846293416853
double pmf2 = dist.ProbabilityMassFunction(k: 5); // 0.069908015870399909
double pmf3 = dist.ProbabilityMassFunction(k: 6); // 0.0810932984096639
double lpmf = dist.LogProbabilityMassFunction(k: 2); // -2.3927801721315989
// Quantile function
int icdf = dist.InverseDistributionFunction(p: cdf); // 2
int icdf1 = dist.InverseDistributionFunction(p: 0.17); // 5
int icdf2 = dist.InverseDistributionFunction(p: 0.46); // 9
int icdf3 = dist.InverseDistributionFunction(p: 0.87); // 15
// Hazard (failure rate) functions
double hf = dist.HazardFunction(x: 4); // 0.062681673912893129
double chf = dist.CumulativeHazardFunction(x: 4); // 0.13461898882526471
// String representation
string str = dist.ToString(CultureInfo.InvariantCulture); // "NegativeBinomial(x; r = 7, p = 0.42)"
#endregion
double[] probabilities = new double[10];
for (int i = 0; i < probabilities.Length; i++)
{
probabilities[i] = dist.DistributionFunction(i);
}
Assert.AreEqual(5.068965517241379, mean);
Assert.AreEqual(9.0, median);
Assert.AreEqual(8.7395957193816862, var);
Assert.AreEqual(0.13461898882526471, chf, 1e-10);
Assert.AreEqual(0.033380251139644379, cdf);
Assert.AreEqual(0.054786846293416853, pmf1);
Assert.AreEqual(0.069908015870399909, pmf2);
Assert.AreEqual(0.0810932984096639, pmf3);
Assert.AreEqual(-3.8297538146412009, lpmf);
Assert.AreEqual(0.062681673912893129, hf);
Assert.AreEqual(0.96661974886035562, ccdf);
Assert.AreEqual(2, icdf);
Assert.AreEqual(5, icdf1);
Assert.AreEqual(9, icdf2);
Assert.AreEqual(15, icdf3);
Assert.AreEqual("NegativeBinomial(x; r = 7, p = 0.42)", str);
var range1 = dist.GetRange(0.95);
var range2 = dist.GetRange(0.99);
var range3 = dist.GetRange(0.01);
Assert.AreEqual(3, range1.Min);
Assert.AreEqual(18.0, range1.Max);
Assert.AreEqual(1, range2.Min);
Assert.AreEqual(23, range2.Max);
Assert.AreEqual(1, range3.Min);
Assert.AreEqual(23, range3.Max);
}