@Test public void testVariance() { System.out.println("variance"); PoissonDistribution instance = new PoissonDistribution(3.5); instance.rand(); assertEquals(3.5, instance.variance(), 1E-7); }
@Override public double variance() { return lambda; }
PoissonDistribution extends DiscreteDistribution implements DiscreteExponentialFamily { @Override public double variance() { return lambda; } }
PoissonDistribution extends DiscreteDistribution implements DiscreteExponentialFamily { @Override public double variance() { return lambda; } PoissonDistribution(double lambda); }
PoissonDistribution extends DiscreteDistribution implements DiscreteExponentialFamily { @Override public double variance() { return lambda; } PoissonDistribution(double lambda); static PoissonDistribution fit(int[] data); @Override int length(); @Override double mean(); @Override double variance(); @Override double sd(); @Override double entropy(); @Override String toString(); @Override double p(int k); @Override double logp(int k); @Override double cdf(double k); @Override double quantile(double p); @Override DiscreteMixture.Component M(int[] x, double[] posteriori); @Override double rand(); }
PoissonDistribution extends DiscreteDistribution implements DiscreteExponentialFamily { @Override public double variance() { return lambda; } PoissonDistribution(double lambda); static PoissonDistribution fit(int[] data); @Override int length(); @Override double mean(); @Override double variance(); @Override double sd(); @Override double entropy(); @Override String toString(); @Override double p(int k); @Override double logp(int k); @Override double cdf(double k); @Override double quantile(double p); @Override DiscreteMixture.Component M(int[] x, double[] posteriori); @Override double rand(); final double lambda; }