/** Chi-Square */
public void testChiSquare() {
System.out.println("Chi-Square");
MultivariatePolyaDistribution.PMF pmf =
new MultivariatePolyaDistribution.PMF(
VectorFactory.getDefault().copyValues(1.0, 200.0, 300.0), 100);
ArrayList<Vector> samples = pmf.sample(RANDOM, NUM_SAMPLES);
MultinomialDistribution.PMF mnd =
new MultinomialDistribution.PMF(
pmf.getParameters().scale(1.0 / pmf.getParameters().norm1()), pmf.getNumTrials());
// for( int i = 0; i < samples.size(); i++ )
// {
// double p1 = pmf.evaluate(samples.get(i));
// double p2 = mnd.evaluate(samples.get(i));
// System.out.println( "Delta = " + (p1-p2) + ", P(" + samples.get(i) + ") = " + p1 +
// ", MND = " + p2 );
// }
// Vector bad = VectorFactory.getDefault().copyValues(4,40,56);
// System.out.println( "MPD: P(bad) = " + pmf.evaluate(bad) );
// System.out.println( "MND: P(bad) = " + mnd.evaluate(bad) );
// ChiSquareConfidence.Statistic chisquare =
// ChiSquareConfidence.evaluateNullHypothesis( Arrays.asList(bad), pmf );
// System.out.println( "Chi-Square: " + chisquare );
}
