public void NormalDistribution_MaximumLikelihood_FromClassifiedSample()
{
// arrange
var distr = new NormalDistribution();
var sample = new ClassifiedSample <double[]>
{
{ new[] { -1.0D, 1.0D, 2.0D }, new Class("A", 0) },
{ new[] { 2.0D, 2.0D, 2.5D }, new Class("A", 0) },
{ new[] { 3.0D, 3.0D, 2.6D }, new Class("B", 1) },
{ new[] { 3.5D, 4.0D, 2.8D }, new Class("B", 1) },
};
// act
var res = distr.FromSample(sample);
var dA1 = res[0][0];
var dA2 = res[0][1];
var dA3 = res[0][2];
var dB1 = res[1][0];
var dB2 = res[1][1];
var dB3 = res[1][2];
// assert
Assert.AreEqual(0.5D, dA1.Mu, EPS);
Assert.AreEqual(1.5D, dA1.Sigma, EPS);
Assert.AreEqual(1.5D, dA2.Mu, EPS);
Assert.AreEqual(0.5D, dA2.Sigma, EPS);
Assert.AreEqual(2.25D, dA3.Mu, EPS);
Assert.AreEqual(0.25D, dA3.Sigma, EPS);
Assert.AreEqual(3.25D, dB1.Mu, EPS);
Assert.AreEqual(0.25D, dB1.Sigma, EPS);
Assert.AreEqual(3.5D, dB2.Mu, EPS);
Assert.AreEqual(0.5D, dB2.Sigma, EPS);
Assert.AreEqual(2.7D, dB3.Mu, EPS);
Assert.AreEqual(0.1D, dB3.Sigma, EPS);
}
public void NormalDistribution_MaximumLikelihood_FromSample()
{
// arrange
var distr = new NormalDistribution();
var sample = new[] { -1.0D, 2.0D, 3.0D, 3.5D };
// act
distr.FromSample(sample);
var pars = distr.Params;
// assert
Assert.AreEqual(1.875D, pars.Mu);
Assert.AreEqual(1.74553000547D, pars.Sigma, EPS);
}
