public void ConstructorTest2()
{
var exp = new ExponentialDistribution(rate: 0.42);
double mean = exp.Mean; // 2.3809523809523809
double median = exp.Median; // 1.6503504299046317
double var = exp.Variance; // 5.6689342403628125
double cdf = exp.DistributionFunction(x: 0.27); // 0.10720652870550407
double pdf = exp.ProbabilityDensityFunction(x: 0.27); // 0.3749732579436883
double lpdf = exp.LogProbabilityDensityFunction(x: 0.27); // -0.98090056770472311
double ccdf = exp.ComplementaryDistributionFunction(x: 0.27); // 0.89279347129449593
double icdf = exp.InverseDistributionFunction(p: cdf); // 0.27
double hf = exp.HazardFunction(x: 0.27); // 0.42
double chf = exp.CumulativeHazardFunction(x: 0.27); // 0.1134
string str = exp.ToString(CultureInfo.InvariantCulture); // Exp(x; λ = 0.42)
Assert.AreEqual(2.3809523809523809, mean);
Assert.AreEqual(1.6503504299046317, median);
Assert.AreEqual(5.6689342403628125, var);
Assert.AreEqual(0.1134, chf);
Assert.AreEqual(0.10720652870550407, cdf);
Assert.AreEqual(0.3749732579436883, pdf);
Assert.AreEqual(-0.98090056770472311, lpdf);
Assert.AreEqual(0.42, hf);
Assert.AreEqual(0.89279347129449593, ccdf);
Assert.AreEqual(0.27, icdf);
Assert.AreEqual("Exp(x; λ = 0.42)", str);
}
public void ConstructorTest2()
{
var exp = new ExponentialDistribution(rate: 0.42);
double mean = exp.Mean; // 2.3809523809523809
double median = exp.Median; // 1.6503504299046317
double var = exp.Variance; // 5.6689342403628125
double cdf = exp.DistributionFunction(x: 0.27); // 0.10720652870550407
double pdf = exp.ProbabilityDensityFunction(x: 0.27); // 0.3749732579436883
double lpdf = exp.LogProbabilityDensityFunction(x: 0.27); // -0.98090056770472311
double ccdf = exp.ComplementaryDistributionFunction(x: 0.27); // 0.89279347129449593
double icdf = exp.InverseDistributionFunction(p: cdf); // 0.27
double hf = exp.HazardFunction(x: 0.27); // 0.42
double chf = exp.CumulativeHazardFunction(x: 0.27); // 0.1134
string str = exp.ToString(CultureInfo.InvariantCulture); // Exp(x; λ = 0.42)
Assert.AreEqual(2.3809523809523809, mean);
Assert.AreEqual(1.6503504299046317, median);
Assert.AreEqual(5.6689342403628125, var);
Assert.AreEqual(0.1134, chf);
Assert.AreEqual(0.10720652870550407, cdf);
Assert.AreEqual(0.3749732579436883, pdf);
Assert.AreEqual(-0.98090056770472311, lpdf);
Assert.AreEqual(0.42, hf);
Assert.AreEqual(0.89279347129449593, ccdf);
Assert.AreEqual(0.27, icdf);
Assert.AreEqual("Exp(x; λ = 0.42)", str);
}
public void ConstructorTest2()
{
var exp = new ExponentialDistribution(rate: 0.42);
double mean = exp.Mean; // 2.3809523809523809
double median = exp.Median; // 1.6503504299046317
double var = exp.Variance; // 5.6689342403628125
double mode = exp.Mode; // 0.0
double cdf = exp.DistributionFunction(x: 0.27); // 0.10720652870550407
double pdf = exp.ProbabilityDensityFunction(x: 0.27); // 0.3749732579436883
double lpdf = exp.LogProbabilityDensityFunction(x: 0.27); // -0.98090056770472311
double ccdf = exp.ComplementaryDistributionFunction(x: 0.27); // 0.89279347129449593
double icdf = exp.InverseDistributionFunction(p: cdf); // 0.27
double hf = exp.HazardFunction(x: 0.27); // 0.42
double chf = exp.CumulativeHazardFunction(x: 0.27); // 0.1134
string str = exp.ToString(CultureInfo.InvariantCulture); // Exp(x; λ = 0.42)
Assert.AreEqual(2.3809523809523809, mean);
Assert.AreEqual(1.6503504299046317, median);
Assert.AreEqual(0.0, mode);
Assert.AreEqual(5.6689342403628125, var);
Assert.AreEqual(0.1134, chf);
Assert.AreEqual(0.10720652870550407, cdf);
Assert.AreEqual(0.3749732579436883, pdf);
Assert.AreEqual(-0.98090056770472311, lpdf);
Assert.AreEqual(0.42, hf);
Assert.AreEqual(0.89279347129449593, ccdf);
Assert.AreEqual(0.27, icdf);
Assert.AreEqual("Exp(x; λ = 0.42)", str);
var range1 = exp.GetRange(0.95);
var range2 = exp.GetRange(0.99);
var range3 = exp.GetRange(0.01);
Assert.AreEqual(0.12212689139892995, range1.Min);
Assert.AreEqual(7.1326958894142622, range1.Max);
Assert.AreEqual(0.023929371079765359, range2.Min);
Assert.AreEqual(10.964690919019265, range2.Max);
Assert.AreEqual(0.023929371079765359, range3.Min);
Assert.AreEqual(10.964690919019265, range3.Max);
}
public void ConstructorTest2()
{
var exp = new ExponentialDistribution(rate: 0.42);
double mean = exp.Mean; // 2.3809523809523809
double median = exp.Median; // 1.6503504299046317
double var = exp.Variance; // 5.6689342403628125
double mode = exp.Mode; // 0.0
double cdf = exp.DistributionFunction(x: 0.27); // 0.10720652870550407
double pdf = exp.ProbabilityDensityFunction(x: 0.27); // 0.3749732579436883
double lpdf = exp.LogProbabilityDensityFunction(x: 0.27); // -0.98090056770472311
double ccdf = exp.ComplementaryDistributionFunction(x: 0.27); // 0.89279347129449593
double icdf = exp.InverseDistributionFunction(p: cdf); // 0.27
double hf = exp.HazardFunction(x: 0.27); // 0.42
double chf = exp.CumulativeHazardFunction(x: 0.27); // 0.1134
string str = exp.ToString(CultureInfo.InvariantCulture); // Exp(x; λ = 0.42)
Assert.AreEqual(2.3809523809523809, mean);
Assert.AreEqual(1.6503504299046317, median);
Assert.AreEqual(0.0, mode);
Assert.AreEqual(5.6689342403628125, var);
Assert.AreEqual(0.1134, chf);
Assert.AreEqual(0.10720652870550407, cdf);
Assert.AreEqual(0.3749732579436883, pdf);
Assert.AreEqual(-0.98090056770472311, lpdf);
Assert.AreEqual(0.42, hf);
Assert.AreEqual(0.89279347129449593, ccdf);
Assert.AreEqual(0.27, icdf);
Assert.AreEqual("Exp(x; λ = 0.42)", str);
var range1 = exp.GetRange(0.95);
var range2 = exp.GetRange(0.99);
var range3 = exp.GetRange(0.01);
Assert.AreEqual(0.12212689139892995, range1.Min);
Assert.AreEqual(7.1326958894142622, range1.Max);
Assert.AreEqual(0.023929371079765359, range2.Min);
Assert.AreEqual(10.964690919019265, range2.Max);
Assert.AreEqual(0.023929371079765359, range3.Min);
Assert.AreEqual(10.964690919019265, range3.Max);
}
public void MedianTest()
{
ExponentialDistribution target = new ExponentialDistribution(2.5);
Assert.AreEqual(target.Median, target.InverseDistributionFunction(0.5));
}
public void MedianTest()
{
ExponentialDistribution target = new ExponentialDistribution(2.5);
Assert.AreEqual(target.Median, target.InverseDistributionFunction(0.5));
}
public static double qnorm(double p)
{
return(_norm.InverseDistributionFunction(p));
}