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package org.apache.commons.math3.distribution;

import org.apache.commons.math3.exception.NotStrictlyPositiveException;

Base interface for multivariate distributions on the reals.
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.
Since:
3.1/**
 * Base interface for multivariate distributions on the reals.
 *
 * 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.
 *
 * @since 3.1
 */
public interface MultivariateRealDistribution {
    
Returns the probability density function (PDF) of this distribution evaluated at the specified point 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. 
Params:
x – Point at which the PDF is evaluated.
Returns:
the value of the probability density function at point x./**
     * Returns the probability density function (PDF) of this distribution
     * evaluated at the specified point {@code x}. In general, the PDF is the
     * derivative of the cumulative distribution function. If the derivative
     * does not exist at {@code x}, then an appropriate replacement should be
     * returned, e.g. {@code Double.POSITIVE_INFINITY}, {@code Double.NaN}, or
     * the limit inferior or limit superior of the difference quotient.
     *
     * @param x Point at which the PDF is evaluated.
     * @return the value of the probability density function at point {@code x}.
     */
    double density(double[] x);

    
Reseeds the random generator used to generate samples.
Params:
seed – Seed with which to initialize the random number generator./**
     * Reseeds the random generator used to generate samples.
     *
     * @param seed Seed with which to initialize the random number generator.
     */
    void reseedRandomGenerator(long seed);

    
Gets the number of random variables of the distribution. It is the size of the array returned by the sample method. 
Returns:
the number of variables./**
     * Gets the number of random variables of the distribution.
     * It is the size of the array returned by the {@link #sample() sample}
     * method.
     *
     * @return the number of variables.
     */
    int getDimension();

    
Generates a random value vector sampled from this distribution.
Returns:
a random value vector./**
     * Generates a random value vector sampled from this distribution.
     *
     * @return a random value vector.
     */
    double[] sample();

    
Generates a list of a random value vectors from the distribution.
Params:
sampleSize – the number of random vectors to generate.
Throws:
NotStrictlyPositiveException –  if sampleSize is not positive.
See Also:
sample()
Returns:
an array representing the random samples./**
     * Generates a list of a random value vectors from the distribution.
     *
     * @param sampleSize the number of random vectors to generate.
     * @return an array representing the random samples.
     * @throws org.apache.commons.math3.exception.NotStrictlyPositiveException
     * if {@code sampleSize} is not positive.
     *
     * @see #sample()
     */
    double[][] sample(int sampleSize) throws NotStrictlyPositiveException;
}