public void BetaMLEFit_RealWeights()
{
double[] x = { 1.0, 0.1, 0.5, 0.3, 0.5, 0.8, 0.6, 0.7, 0.9, 0.9, 0.9 };
int[] w = { 0, 1, 1, 1, 0, 1, 1, 1, 1, 1, 2 };
BetaDistribution target = new BetaDistribution(0, 1);
var options = new BetaOptions()
{
Method = BetaEstimationMethod.MaximumLikelihood
};
target.Fit(x, w.ToDouble(), options);
Assert.AreEqual(1.1401591160220996, target.Alpha);
Assert.AreEqual(0.58735469613259694, target.Beta);
}
public void BetaMLEFit_IntWeights()
{
double[] x = { 1.0, 0.1, 0.5, 0.3, 0.5, 0.8, 0.6, 0.7, 0.9, 0.9, 0.9 };
int[] w = { 0, 1, 1, 1, 0, 1, 1, 1, 1, 1, 2 };
BetaDistribution target = new BetaDistribution(0, 1);
var options = new BetaOptions()
{
Method = BetaEstimationMethod.MaximumLikelihood
};
target.Fit(x, w, options);
Assert.AreEqual(1.1810718232044195, target.Alpha);
Assert.AreEqual(0.60843093922651903, target.Beta, 1e-10);
}
public void BetaMLEFitTest1()
{
double[] x = samples;
{
BetaDistribution target = new BetaDistribution(0, 1);
var options = new BetaOptions() { Method = BetaEstimationMethod.Moments };
target.Fit(x, options);
Assert.AreEqual(1, target.Alpha, 0.04);
Assert.AreEqual(3, target.Beta, 0.5);
}
{
BetaDistribution target = new BetaDistribution(0, 1);
var options = new BetaOptions() { Method = BetaEstimationMethod.MaximumLikelihood };
target.Fit(x, options);
Assert.AreEqual(1, target.Alpha, 0.04);
Assert.AreEqual(3, target.Beta, 0.55);
}
}
