@Test public void testMean() { System.out.println("mean"); BetaDistribution instance = new BetaDistribution(2, 5); instance.rand(); assertEquals(0.2857143, instance.mean(), 1E-7); }
@Override public double mean() { return mean; }
BetaDistribution extends AbstractDistribution implements ExponentialFamily { @Override public double mean() { return mean; } }
BetaDistribution extends AbstractDistribution implements ExponentialFamily { @Override public double mean() { return mean; } BetaDistribution(double alpha, double beta); }
BetaDistribution extends AbstractDistribution implements ExponentialFamily { @Override public double mean() { return mean; } BetaDistribution(double alpha, double beta); static BetaDistribution fit(double[] data); double getAlpha(); double getBeta(); @Override int length(); @Override double mean(); @Override double variance(); @Override double entropy(); @Override String toString(); @Override double p(double x); @Override double logp(double x); @Override double cdf(double x); @Override double quantile(double p); @Override Mixture.Component M(double[] x, double[] posteriori); @Override double rand(); }
BetaDistribution extends AbstractDistribution implements ExponentialFamily { @Override public double mean() { return mean; } BetaDistribution(double alpha, double beta); static BetaDistribution fit(double[] data); double getAlpha(); double getBeta(); @Override int length(); @Override double mean(); @Override double variance(); @Override double entropy(); @Override String toString(); @Override double p(double x); @Override double logp(double x); @Override double cdf(double x); @Override double quantile(double p); @Override Mixture.Component M(double[] x, double[] posteriori); @Override double rand(); final double alpha; final double beta; }