public void TestIntegrateDistribution(double[] x, double[] mu, double[,] sigma, double expected, double error)
{
var sampler = new MultivariateNormalSampler.Builder(mu, sigma).Build(new ReducedThreeFry4X64(1));
var actual = SamplerTester.IntegrateMultivariateCdf(sampler, x, Trials);
Assert.AreEqual(actual, expected, error);
}
public void TestIntegrateDistribution(double[] x, double[,] sigma, double expected, double error)
{
var sampler = new GaussianCopulaSampler.Builder(sigma).Build(new ReducedThreeFry4X64(1));
var actual = SamplerTester.IntegrateMultivariateCdf(sampler, x, 1000000);
Assert.AreEqual(expected, actual, error);
}
public void TestGetIntegrateDistribution(double x, double mean, double sigma, double error)
{
var sampler = new LogNormalSampler(new ReducedThreeFry4X64(1), mean, sigma);
var referenceDistribution = new LogNormalDistribution(mean, sigma);
SamplerTester.TestIntegrateDistribution(x, sampler, referenceDistribution, error);
}
public void TestGetIntegrateDistribution(double x, double min, double max, double error)
{
var sampler = new UniformRealSampler(new ReducedThreeFry4X64(1), min, max);
var referenceDistribution = new UniformRealDistribution(min, max);
SamplerTester.TestIntegrateDistribution(x, sampler, referenceDistribution, error);
}
