MultivariateNormalDistribution extends AbstractMultivariateRealDistribution { public double[] getMeans() { return MathArrays.copyOf(means); } MultivariateNormalDistribution(final double[] means,
                                          final double[][] covariances);  MultivariateNormalDistribution(RandomGenerator rng,
                                          final double[] means,
                                          final double[][] covariances); double[] getMeans(); RealMatrix getCovariances(); double density(final double[] vals); double[] getStandardDeviations(); @Override double[] sample();  }
@Test public void testGetMean() { final double[] mu = { -1.5, 2 }; final double[][] sigma = { { 2, -1.1 }, { -1.1, 2 } }; final MultivariateNormalDistribution d = new MultivariateNormalDistribution(mu, sigma); final double[] m = d.getMeans(); for (int i = 0; i < m.length; i++) { Assert.assertEquals(mu[i], m[i], 0); } }