public void FitTest6()
{
UnivariateDiscreteDistribution target = CreateUnivariateDiscreteDistribution();
double[] observations = { 0, 1, 1, 1, 1 };
target.Fit(observations);
double mean = Accord.Statistics.Tools.Mean(observations);
Assert.AreEqual(mean, target.Mean);
}
public void FitTest7()
{
UnivariateDiscreteDistribution target = CreateUnivariateDiscreteDistribution();
double[] observations = { 0, 1, 1, 1, 1 };
double[] weights = { 0.125, 0.125, 0.25, 0.25, 0.25 };
target.Fit(observations, weights);
double mean = Accord.Statistics.Tools.WeightedMean(observations, weights);
Assert.AreEqual(mean, target.Mean);
}
public void FitTest4()
{
UnivariateDiscreteDistribution target = CreateUnivariateDiscreteDistribution();
double[] observations = { 0, 1, 1, 1, 1 };
IFittingOptions options = null;
target.Fit(observations, options);
double mean = Measures.Mean(observations);
Assert.AreEqual(mean, target.Mean);
}
public void ProbabilityMassFunctionTest()
{
UnivariateDiscreteDistribution target = CreateUnivariateDiscreteDistribution();
double p = 0.42;
double q = 1 - p;
Assert.AreEqual(q, target.ProbabilityMassFunction(0));
Assert.AreEqual(p, target.ProbabilityMassFunction(1));
double[] observations = { 0, 1, 0, 0, 1, 0 };
target.Fit(observations);
p = target.Mean;
q = 1 - p;
Assert.AreEqual(q, target.ProbabilityMassFunction(0));
Assert.AreEqual(p, target.ProbabilityMassFunction(1));
}
public void EntropyTest()
{
UnivariateDiscreteDistribution target = CreateUnivariateDiscreteDistribution();
double q = 0.42;
double p = 1 - q;
double actual = target.Entropy;
double expected = -q *System.Math.Log(q) - p * System.Math.Log(p);
Assert.AreEqual(expected, actual);
target.Fit(new double[] { 0, 1, 0, 0, 1, 0 });
q = target.Mean;
p = 1 - q;
actual = target.Entropy;
expected = -q *System.Math.Log(q) - p * System.Math.Log(p);
Assert.AreEqual(expected, actual);
}