public void Bug2811()
{
ChiSquaredDistribution d = new ChiSquaredDistribution(1798);
double x = d.InverseLeftProbability(0.975);
Console.WriteLine(x);
}
public void FisherTest()
{
// we will need a RNG
Random rng = new Random(314159);
int n1 = 1;
int n2 = 2;
// define chi squared distributions
ContinuousDistribution d1 = new ChiSquaredDistribution(n1);
ContinuousDistribution d2 = new ChiSquaredDistribution(n2);
// create a sample of chi-squared variates
Sample s = new Sample();
for (int i = 0; i < 250; i++)
{
double x1 = d1.InverseLeftProbability(rng.NextDouble());
double x2 = d2.InverseLeftProbability(rng.NextDouble());
double x = (x1 / n1) / (x2 / n2);
s.Add(x);
}
// it should match a Fisher distribution with the appropriate parameters
ContinuousDistribution f0 = new FisherDistribution(n1, n2);
TestResult t0 = s.KuiperTest(f0);
Console.WriteLine(t0.LeftProbability);
Assert.IsTrue(t0.LeftProbability < 0.95);
// it should be distinguished from a Fisher distribution with different parameters
ContinuousDistribution f1 = new FisherDistribution(n1 + 1, n2);
TestResult t1 = s.KuiperTest(f1);
Console.WriteLine(t1.LeftProbability);
Assert.IsTrue(t1.LeftProbability > 0.95);
}