public void FitTest6()
{
MultivariateContinuousDistribution target = CreateMultivariateContinuousDistribution(); // TODO: Initialize to an appropriate value
double[][] observations =
{
new double[] { 1, 2 },
new double[] { 3, 2 },
new double[] { 2, 3 },
new double[] { 1, 2 },
};
target.Fit(observations);
double[] expectedMean = { 1.75, 2.25 };
double[,] expectedCov =
{
{ 0.91666666666666663, 0.083333333333333329 },
{ 0.083333333333333329, 0.25 },
};
Assert.IsTrue(expectedMean.IsEqual(target.Mean));
Assert.IsTrue(expectedCov.IsEqual(target.Covariance));
Assert.IsTrue(expectedCov.Diagonal().IsEqual(target.Variance));
double[] x = { 0.4, 2 };
double expected = 0.120833904312578;
double actual = target.ProbabilityDensityFunction(x);
Assert.AreEqual(expected, actual, 1e-10);
}
public void FitTest7()
{
MultivariateContinuousDistribution target = CreateMultivariateContinuousDistribution();
double[][] observations =
{
new double[] { 1, 2 },
new double[] { 3, 2 },
new double[] { 2, 3 },
new double[] { 1, 2 },
};
double[] weights = { 0.125, 0.125, 0.25, 0.5 };
target.Fit(observations, weights);
double[] expectedMean = { 1.5, 2.25 };
double[,] expectedCov =
{
{ 0.76190476190476186, 0.19047619047619047 },
{ 0.19047619047619047, 0.2857142857142857 },
};
Assert.IsTrue(expectedMean.IsEqual(target.Mean));
Assert.IsTrue(expectedCov.IsEqual(target.Covariance));
Assert.IsTrue(Matrix.Diagonal(expectedCov).IsEqual(target.Variance));
double[] x = { 0.4, 2 };
double expected = 0.168681501947055;
double actual = target.ProbabilityDensityFunction(x);
Assert.AreEqual(expected, actual, 1e-10);
}
public void DimensionTest()
{
MultivariateContinuousDistribution target = CreateMultivariateContinuousDistribution();
int actual = target.Dimension;
int expected = 2;
Assert.AreEqual(expected, actual);
}
public void MeanTest()
{
MultivariateContinuousDistribution target = CreateMultivariateContinuousDistribution();
double[] actual = target.Mean;
double[] expected = { 0.2, 4.2 };
Assert.IsTrue(expected.IsEqual(actual));
}
public void VarianceTest()
{
MultivariateContinuousDistribution target = CreateMultivariateContinuousDistribution();
double[] actual = target.Variance;
double[] expected = { 1.2, 2.3 };
Assert.IsTrue(expected.IsEqual(actual));
}
public void ProbabilityDensityFunctionTest()
{
MultivariateContinuousDistribution target = CreateMultivariateContinuousDistribution();
double[] x = { 0.4, 2 };
double expected = 0.032309150392899;
double actual = target.ProbabilityDensityFunction(x);
Assert.AreEqual(expected, actual, 1e-10);
}
public void CovarianceTest()
{
MultivariateContinuousDistribution target = CreateMultivariateContinuousDistribution();
double[,] actual = target.Covariance;
double[,] expected =
{
{ 1.2, 0.1 },
{ 0.1, 2.3 },
};
Assert.IsTrue(expected.IsEqual(actual));
}
public void FitTest5()
{
MultivariateContinuousDistribution target = CreateMultivariateContinuousDistribution(); // TODO: Initialize to an appropriate value
double[][] observations =
{
new double[] { 1, 1 },
new double[] { 1, 1 },
};
double[] weights = { 0.50, 0.50 };
bool thrown;
IFittingOptions options = new NormalOptions()
{
Regularization = 0.1
};
thrown = false;
try
{
target.Fit(observations, weights);
}
catch
{
thrown = true;
}
Assert.AreEqual(true, thrown);
thrown = false;
try
{
target.Fit(observations, weights, options);
}
catch
{
thrown = true;
}
Assert.AreEqual(false, thrown);
}
public void FitTest2()
{
IDistribution target = CreateMultivariateContinuousDistribution();
double[][] observations =
{
new double[] { 1, 2 },
new double[] { 3, 2 },
new double[] { 2, 3 },
new double[] { 1, 2 },
};
target.Fit(observations);
double[] expectedMean = Measures.Mean(observations, dimension: 0);
double[][] expectedCov = Measures.Covariance(observations, expectedMean);
MultivariateContinuousDistribution actual = target as MultivariateContinuousDistribution;
Assert.IsTrue(expectedMean.IsEqual(actual.Mean));
Assert.IsTrue(expectedCov.IsEqual(actual.Covariance));
}
public void FitTest3()
{
IDistribution target = CreateMultivariateContinuousDistribution();
double[][] observations =
{
new double[] { 1, 2 },
new double[] { 3, 2 },
new double[] { 2, 3 },
new double[] { 1, 2 },
};
target.Fit(observations);
double[] expectedMean = Accord.Statistics.Tools.Mean(observations);
double[,] expectedCov = Accord.Statistics.Tools.Covariance(observations, expectedMean);
MultivariateContinuousDistribution actual = target as MultivariateContinuousDistribution;
Assert.IsTrue(expectedMean.IsEqual(actual.Mean));
Assert.IsTrue(expectedCov.IsEqual(actual.Covariance));
}
