AbstractMultivariateRealDistribution, MixtureMultivariateNormalDistribution, MixtureMultivariateRealDistribution, MultivariateNormalDistributionpublic interface MultivariateRealDistribution
This is based largely on the RealDistribution interface, but cumulative distribution functions are not required because they are often quite difficult to compute for multivariate distributions.
| Modifier and Type | Method | Description | 
|---|---|---|
double | 
density(double[] x) | 
 Returns the probability density function (PDF) of this distribution
 evaluated at the specified point  
x. | 
int | 
getDimension() | 
 Gets the number of random variables of the distribution. 
 | 
void | 
reseedRandomGenerator(long seed) | 
 Reseeds the random generator used to generate samples. 
 | 
double[] | 
sample() | 
 Generates a random value vector sampled from this distribution. 
 | 
double[][] | 
sample(int sampleSize) | 
 Generates a list of a random value vectors from the distribution. 
 | 
double density(double[] x)
x. In general, the PDF is the
 derivative of the cumulative distribution function. If the derivative
 does not exist at x, then an appropriate replacement should be
 returned, e.g. Double.POSITIVE_INFINITY, Double.NaN, or
 the limit inferior or limit superior of the difference quotient.x - Point at which the PDF is evaluated.x.void reseedRandomGenerator(long seed)
seed - Seed with which to initialize the random number generator.int getDimension()
sample
 method.double[] sample()
double[][] sample(int sampleSize)
           throws MathIllegalArgumentException
sampleSize - the number of random vectors to generate.MathIllegalArgumentException - if sampleSize is not positive.sample()Copyright © 2016–2018 Hipparchus.org. All rights reserved.