| public DistributionFunction ( double x ) : double | ||
| x | double | A single point in the distribution range. |
| return | double | |
public void TrapezoidalDistributionConstructorTest()
{
double x = 0.75d;
double a = 0;
double b = (1.0d/3.0d);
double c = (2.0d/3.0d);
double d = 1.0d;
double n1 = 2.0d;
double n3 = 2.0d;
var trapDist = new TrapezoidalDistribution(a, b, c, d, n1, n3);
double mean = trapDist.Mean; //0.62499999999999989
double variance = trapDist.Variance; //0.37103174603174593
double pdf = trapDist.ProbabilityDensityFunction(x); //1.1249999999999998
double cdf = trapDist.DistributionFunction(x); //1.28125
string tostr = trapDist.ToString("N2", CultureInfo.InvariantCulture);
Assert.AreEqual(mean, 0.625d, 0.00000001);
Assert.AreEqual(variance, 0.37103175d, 0.00000001);
Assert.AreEqual(pdf, 1.125, 0.000000001, "should match output from dtrapezoid in R");
Assert.AreEqual(cdf, 1.28125,0.000000001);
Assert.AreEqual(tostr, "Trapezoidal(x; a = 0.00, b = 0.33, c = 0.67, d = 1.00, n1 = 2.00, n3 = 2.00, α = 1.00)");
//Verified using R package 'trapezoid'
}
public void DocumentationTest1()
{
// Create a new trapezoidal distribution with linear growth between
// 0 and 2, stability between 2 and 8, and decrease between 8 and 10.
//
//
// +-----------+
// /| |\
// / | | \
// / | | \
// -------+---+-----------+---+-------
// ... 0 2 4 6 8 10 ...
//
var trapz = new TrapezoidalDistribution(a: 0, b: 2, c: 8, d: 10, n1: 1, n3: 1);
double mean = trapz.Mean; // 2.25
double median = trapz.Median; // 3.0
double mode = trapz.Mode; // 3.1353457616424696
double var = trapz.Variance; // 17.986666666666665
double cdf = trapz.DistributionFunction(x: 1.4); // 0.13999999999999999
double pdf = trapz.ProbabilityDensityFunction(x: 1.4); // 0.10000000000000001
double lpdf = trapz.LogProbabilityDensityFunction(x: 1.4); // -2.3025850929940455
double ccdf = trapz.ComplementaryDistributionFunction(x: 1.4); // 0.85999999999999999
double icdf = trapz.InverseDistributionFunction(p: cdf); // 1.3999999999999997
double hf = trapz.HazardFunction(x: 1.4); // 0.11627906976744187
double chf = trapz.CumulativeHazardFunction(x: 1.4); // 0.15082288973458366
string str = trapz.ToString(CultureInfo.InvariantCulture); // Trapezoidal(x; a=0, b=2, c=8, d=10, n1=1, n3=1, α = 1)
Assert.AreEqual(2.25, mean);
Assert.AreEqual(3.0, median);
Assert.AreEqual(3.1353457616424696, mode);
Assert.AreEqual(17.986666666666665, var);
Assert.AreEqual(0.15082288973458366, chf);
Assert.AreEqual(0.13999999999999999, cdf);
Assert.AreEqual(0.10000000000000001, pdf);
Assert.AreEqual(-2.3025850929940455, lpdf);
Assert.AreEqual(0.11627906976744187, hf);
Assert.AreEqual(0.85999999999999999, ccdf);
Assert.AreEqual(1.3999999999999997, icdf);
Assert.AreEqual("Trapezoidal(x; a = 0, b = 2, c = 8, d = 10, n1 = 1, n3 = 1, α = 1)", str);
var range1 = trapz.GetRange(0.95);
var range2 = trapz.GetRange(0.99);
var range3 = trapz.GetRange(0.01);
Assert.AreEqual(0.50000000000000044, range1.Min);
Assert.AreEqual(5.7000000000000002, range1.Max);
Assert.AreEqual(0.10000000000000009, range2.Min);
Assert.AreEqual(5.9400000000000004, range2.Max);
Assert.AreEqual(0.10000000000000001, range3.Min);
Assert.AreEqual(5.9400000000000004, range3.Max);
}