@Test public void testLength() { System.out.println("length"); GaussianDistribution instance = new GaussianDistribution(3.0, 2.0); instance.rand(); assertEquals(2, instance.length()); }
@Override public int length() { return 2; }
GaussianDistribution extends AbstractDistribution implements ExponentialFamily { @Override public int length() { return 2; } }
GaussianDistribution extends AbstractDistribution implements ExponentialFamily { @Override public int length() { return 2; } GaussianDistribution(double mu, double sigma); }
GaussianDistribution extends AbstractDistribution implements ExponentialFamily { @Override public int length() { return 2; } GaussianDistribution(double mu, double sigma); static GaussianDistribution fit(double[] data); static GaussianDistribution getInstance(); @Override int length(); @Override double mean(); @Override double variance(); @Override double sd(); @Override double entropy(); @Override String toString(); @Override double rand(); double randInverseCDF(); @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); }
GaussianDistribution extends AbstractDistribution implements ExponentialFamily { @Override public int length() { return 2; } GaussianDistribution(double mu, double sigma); static GaussianDistribution fit(double[] data); static GaussianDistribution getInstance(); @Override int length(); @Override double mean(); @Override double variance(); @Override double sd(); @Override double entropy(); @Override String toString(); @Override double rand(); double randInverseCDF(); @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); final double mu; final double sigma; }