fr.cnes.sirius.patrius.math.distribution

Class AbstractRealDistribution

java.lang.Object

fr.cnes.sirius.patrius.math.distribution.AbstractRealDistribution

All Implemented Interfaces:

RealDistribution, Serializable

Direct Known Subclasses:

BetaDistribution, CauchyDistribution, ChiSquaredDistribution, EmpiricalDistribution, ExponentialDistribution, FDistribution, GammaDistribution, LogNormalDistribution, NormalDistribution, TDistribution, TriangularDistribution, UniformRealDistribution, WeibullDistribution

public abstract class AbstractRealDistribution
extends Object
implements RealDistribution, Serializable

Base class for probability distributions on the reals. Default implementations are provided for some of the methods that do not vary from distribution to distribution.

Since:

3.0

Version:

$Id: AbstractRealDistribution.java 18108 2017-10-04 06:45:27Z bignon $

See Also:

Serialized Form

Field Summary

Fields

Modifier and Type	Field and Description
protected RandomGenerator	random RNG instance used to generate samples from the distribution.
static double	SOLVER_DEFAULT_ABSOLUTE_ACCURACY Default accuracy.

Constructor Summary

Constructors

Modifier	Constructor and Description
protected	AbstractRealDistribution(RandomGenerator rng)

Method Summary

Modifier and Type	Method and Description
protected double	getSolverAbsoluteAccuracy() Returns the solver absolute accuracy for inverse cumulative computation.
double	inverseCumulativeProbability(double p) The default implementation returns RealDistribution.getSupportLowerBound() for p = 0, RealDistribution.getSupportUpperBound() for p = 1.
double	probability(double x) For a random variable X whose values are distributed according to this distribution, this method returns P(X = x).
double	probability(double x0, double x1) For a random variable X whose values are distributed according to this distribution, this method returns P(x0 < X <= x1).
void	reseedRandomGenerator(long seed) Reseed the random generator used to generate samples.
double	sample() Generate a random value sampled from this distribution.
double[]	sample(int sampleSize) Generate a random sample from the distribution.

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Methods inherited from interface fr.cnes.sirius.patrius.math.distribution.RealDistribution

cumulativeProbability, density, getNumericalMean, getNumericalVariance, getSupportLowerBound, getSupportUpperBound, isSupportConnected

Field Detail

SOLVER_DEFAULT_ABSOLUTE_ACCURACY

public static final double SOLVER_DEFAULT_ABSOLUTE_ACCURACY

Default accuracy.

See Also:

Constant Field Values

random

protected final RandomGenerator random

RNG instance used to generate samples from the distribution.

Since:

3.1

Constructor Detail

AbstractRealDistribution

protected AbstractRealDistribution(RandomGenerator rng)

Parameters:

rng - Random number generator.

Since:

3.1

Method Detail

probability

public double probability(double x0,
                          double x1)

For a random variable X whose values are distributed according to this distribution, this method returns P(x0 < X <= x1).

Specified by:

probability in interface RealDistribution

Parameters:

x0 - Lower bound (excluded).

x1 - Upper bound (included).

Returns:

the probability that a random variable with this distribution takes a value between x0 and x1, excluding the lower and including the upper endpoint.

Throws:

NumberIsTooLargeException - if x0 > x1. The default implementation uses the identity P(x0 < X <= x1) = P(X <= x1) - P(X <= x0)

Since:

3.1

inverseCumulativeProbability

public double inverseCumulativeProbability(double p)

The default implementation returns

• RealDistribution.getSupportLowerBound() for p = 0,
• RealDistribution.getSupportUpperBound() for p = 1.

Specified by:

inverseCumulativeProbability in interface RealDistribution

Parameters:

p - the cumulative probability

Returns:

the smallest p-quantile of this distribution (largest 0-quantile for p = 0)

getSolverAbsoluteAccuracy

protected double getSolverAbsoluteAccuracy()

Returns the solver absolute accuracy for inverse cumulative computation. You can override this method in order to use a Brent solver with an absolute accuracy different from the default.

Returns:

the maximum absolute error in inverse cumulative probability estimates

reseedRandomGenerator

public void reseedRandomGenerator(long seed)

Reseed the random generator used to generate samples.

Specified by:

reseedRandomGenerator in interface RealDistribution

Parameters:

seed - the new seed

sample

public double sample()

Generate a random value sampled from this distribution. The default implementation uses the inversion method.

Specified by:

sample in interface RealDistribution

Returns:

a random value.

sample

public double[] sample(int sampleSize)

Generate a random sample from the distribution. The default implementation generates the sample by calling sample() in a loop.

Specified by:

sample in interface RealDistribution

Parameters:

sampleSize - the number of random values to generate

Returns:

an array representing the random sample

probability

public double probability(double x)

For a random variable X whose values are distributed according to this distribution, this method returns P(X = x). In other words, this method represents the probability mass function (PMF) for the distribution.

Specified by:

probability in interface RealDistribution

Parameters:

x - the point at which the PMF is evaluated

Returns:

zero.

Since:

3.1