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); }