public void ConstructorTest()
{
WeibullDistribution n = new WeibullDistribution(0.807602, 12.5);
Assert.AreEqual(14.067993598321863, n.Mean);
Assert.AreEqual(17.552908226174811, n.StandardDeviation);
Assert.IsFalse(Double.IsNaN(n.Mean));
Assert.IsFalse(Double.IsNaN(n.Variance));
}
public void ConstructorTest2()
{
var weilbull = new WeibullDistribution(scale: 0.42, shape: 1.2);
double mean = weilbull.Mean; // 0.39507546046784414
double median = weilbull.Median; // 0.30945951550913292
double var = weilbull.Variance; // 0.10932249666369542
double mode = weilbull.Mode; // 0.094360430821809421
double cdf = weilbull.DistributionFunction(x: 1.4); // 0.98560487188700052
double pdf = weilbull.ProbabilityDensityFunction(x: 1.4); // 0.052326687031379278
double lpdf = weilbull.LogProbabilityDensityFunction(x: 1.4); // -2.9502487697674415
double ccdf = weilbull.ComplementaryDistributionFunction(x: 1.4); // 0.22369885565908001
double icdf = weilbull.InverseDistributionFunction(p: cdf); // 1.400000001051205
double hf = weilbull.HazardFunction(x: 1.4); // 1.1093328057258516
double chf = weilbull.CumulativeHazardFunction(x: 1.4); // 1.4974545260150962
string str = weilbull.ToString(CultureInfo.InvariantCulture); // Weibull(x; λ = 0.42, k = 1.2)
double imedian = weilbull.InverseDistributionFunction(p: 0.5);
Assert.AreEqual(0.39507546046784414, mean);
Assert.AreEqual(0.30945951550913292, median);
Assert.AreEqual(0.094360430821809421, mode, 1e-10);
Assert.AreEqual(0.3094595, imedian, 1e-5);
Assert.AreEqual(0.10932249666369542, var);
Assert.AreEqual(1.4974545260150962, chf);
Assert.AreEqual(0.98560487188700052, cdf);
Assert.AreEqual(0.052326687031379278, pdf);
Assert.AreEqual(-2.9502487697674415, lpdf);
Assert.AreEqual(1.1093328057258516, hf);
Assert.AreEqual(0.22369885565908001, ccdf);
Assert.AreEqual(1.40, icdf, 1e-6);
Assert.AreEqual("Weibull(x; λ = 0.42, k = 1.2)", str);
var range1 = weilbull.GetRange(0.95);
var range2 = weilbull.GetRange(0.99);
var range3 = weilbull.GetRange(0.01);
Assert.AreEqual(0.035342687605397792, range1.Min);
Assert.AreEqual(1.0479366931850318, range1.Max);
Assert.AreEqual(0.0090865355213001313, range2.Min);
Assert.AreEqual(1.4995260942223139, range2.Max);
Assert.AreEqual(0.0090865355213001677, range3.Min);
Assert.AreEqual(1.4995260942223139, range3.Max);
}
public void ProbabilityDistributionTest()
{
WeibullDistribution n = new WeibullDistribution(0.80, 12.5);
double[] expected =
{
0.0,
0.09289322,
0.0733005,
0.06186956,
0.0537782,
0.0475457
};
double[] actual = new double[expected.Length];
for (int i = 0; i < actual.Length; i++)
actual[i] = n.ProbabilityDensityFunction(i);
for (int i = 0; i < actual.Length; i++)
{
Assert.AreEqual(expected[i], actual[i], 1e-5);
Assert.IsFalse(double.IsNaN(actual[i]));
}
}
public void CumulativeDistributionTest()
{
WeibullDistribution n = new WeibullDistribution(0.80, 12.5);
double[] expected =
{
Double.PositiveInfinity,
0.1241655,
0.2061272,
0.2733265,
0.3309536,
0.3814949,
};
double[] actual = new double[expected.Length];
for (int i = 0; i < actual.Length; i++)
actual[i] = n.DistributionFunction(i);
for (int i = 0; i < actual.Length; i++)
{
Assert.AreEqual(expected[i], actual[i], 1e-6);
Assert.IsFalse(double.IsNaN(actual[i]));
}
}
public void MedianTest()
{
WeibullDistribution target = new WeibullDistribution(1.52, 0.6);
Assert.AreEqual(target.Median, target.InverseDistributionFunction(0.5), 1e-8);
}