public void FitTest()
{
double[][] observations =
{
new double[] { 0.1000, -0.2000 },
new double[] { 0.4000, 0.6000 },
new double[] { 2.0000, 0.2000 },
new double[] { 2.0000, 0.3000 }
};
var target = new MultivariateEmpiricalDistribution(observations);
double[] weigths = { 0.25, 0.25, 0.25, 0.25 };
bool thrown = false;
try
{
target.Fit(observations, weigths);
}
catch (ArgumentException)
{
thrown = true;
}
Assert.IsTrue(thrown);
}
public void FitTest2()
{
double[][] observations =
{
new double[] { 0.1000, -0.2000 },
new double[] { 0.4000, 0.6000 },
new double[] { 2.0000, 0.2000 },
new double[] { 2.0000, 0.3000 }
};
double[] mean = Accord.Statistics.Tools.Mean(observations);
double[,] cov = Accord.Statistics.Tools.Covariance(observations);
var target = new MultivariateEmpiricalDistribution(observations);
target.Fit(observations);
Assert.IsTrue(Matrix.IsEqual(mean, target.Mean));
Assert.IsTrue(Matrix.IsEqual(cov, target.Covariance, 1e-10));
}
public void FitTest()
{
double[] original = { 5, 5, 1, 4, 1, 2, 2, 3, 3, 3, 4, 3, 3, 3, 4, 3, 2, 3 };
var distribution = new MultivariateEmpiricalDistribution(original.ToJagged());
int[] weights = { 2, 1, 1, 1, 2, 3, 1, 3, 1, 1, 1, 1 };
double[] sources = { 5, 1, 4, 1, 2, 3, 4, 3, 4, 3, 2, 3 };
double[][] samples = sources.ToJagged();
var target = new MultivariateEmpiricalDistribution(Jagged.Zeros(1, 1));
target.Fit(samples, weights);
Assert.AreEqual(distribution.Mean[0], target.Mean[0]);
Assert.AreEqual(distribution.Median[0], target.Median[0]);
Assert.AreEqual(distribution.Mode[0], target.Mode[0]);
Assert.AreEqual(distribution.Smoothing[0, 0], target.Smoothing[0, 0]);
Assert.AreEqual(distribution.Variance[0], target.Variance[0]);
Assert.IsTrue(target.Weights.IsEqual(weights.Divide(weights.Sum())));
Assert.AreEqual(target.Samples, samples);
for (double x = 0; x < 6; x += 0.1)
{
double actual, expected;
expected = distribution.ComplementaryDistributionFunction(x);
actual = target.ComplementaryDistributionFunction(x);
Assert.AreEqual(expected, actual);
expected = distribution.DistributionFunction(x);
actual = target.DistributionFunction(x);
Assert.AreEqual(expected, actual);
expected = distribution.LogProbabilityDensityFunction(x);
actual = target.LogProbabilityDensityFunction(x);
Assert.AreEqual(expected, actual, 1e-15);
expected = distribution.ProbabilityDensityFunction(x);
actual = target.ProbabilityDensityFunction(x);
Assert.AreEqual(expected, actual, 1e-15);
}
}
