public void GenerateTest()
{
InverseGaussianDistribution target = new InverseGaussianDistribution(1, 1);
double[] samples = target.Generate(1000000);
InverseGaussianDistribution actual = new InverseGaussianDistribution(5, 5);
actual.Fit(samples);
Assert.AreEqual(1, actual.Mean, 0.01);
Assert.AreEqual(1, actual.Shape, 0.01);
}
public void GenerateTest2()
{
InverseGaussianDistribution target = new InverseGaussianDistribution(5, 2);
double[] samples = target.Generate(1000000);
var actual = InverseGaussianDistribution.Estimate(samples);
actual.Fit(samples);
Assert.AreEqual(5, actual.Mean, 0.01);
Assert.AreEqual(2, actual.Shape, 0.01);
}
public void GenerateTest2()
{
Accord.Math.Tools.SetupGenerator(0);
InverseGaussianDistribution target = new InverseGaussianDistribution(5, 2);
double[] samples = target.Generate(10000000);
var actual = InverseGaussianDistribution.Estimate(samples);
actual.Fit(samples);
Assert.AreEqual(5, actual.Mean, 1e-3);
Assert.AreEqual(2, actual.Shape, 1e-3);
}
public void GenerateTest3()
{
InverseGaussianDistribution target = new InverseGaussianDistribution(4, 2);
double[] samples = new double[1000000];
for (int i = 0; i < samples.Length; i++)
{
samples[i] = target.Generate();
}
var actual = InverseGaussianDistribution.Estimate(samples);
actual.Fit(samples);
Assert.AreEqual(4, actual.Mean, 0.01);
Assert.AreEqual(2, actual.Shape, 0.01);
}
public void GenerateTest4()
{
Accord.Math.Random.Generator.Seed = 0;
InverseGaussianDistribution target = new InverseGaussianDistribution(0.4, 0.2);
double[] samples = new double[10000000];
for (int i = 0; i < samples.Length; i++)
{
samples[i] = target.Generate();
}
var actual = InverseGaussianDistribution.Estimate(samples);
actual.Fit(samples);
Assert.AreEqual(0.4, actual.Mean, 1e-3);
Assert.AreEqual(0.2, actual.Shape, 1e-3);
}
