org.apache.commons.math3.distribution
Class AbstractRealDistribution

java.lang.Object
  org.apache.commons.math3.distribution.AbstractRealDistribution

All Implemented Interfaces:

Serializable, RealDistribution

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 17623 2017-05-19 07:45:31Z bignon $

See Also:

Serialized Form

Field Summary

protected RandomGenerator	random RNG instance used to generate samples from the distribution.
protected RandomDataImpl	randomData Deprecated. As of 3.1, to be removed in 4.0. Please use the random instance variable instead.
static double	SOLVER_DEFAULT_ABSOLUTE_ACCURACY Default accuracy.

Constructor Summary

protected	AbstractRealDistribution() Deprecated. As of 3.1, to be removed in 4.0. Please use AbstractRealDistribution(RandomGenerator) instead.
protected	AbstractRealDistribution(RandomGenerator rng)

Method Summary

double	cumulativeProbability(double x0, double x1) Deprecated. As of 3.1 (to be removed in 4.0). Please use probability(double,double) instead.
protected double	getSolverAbsoluteAccuracy() Returns the solver absolute accuracy for inverse cumulative computation.
double	inverseCumulativeProbability(double p) Computes the quantile function of this distribution.
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 org.apache.commons.math3.distribution.RealDistribution

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

Field Detail

SOLVER_DEFAULT_ABSOLUTE_ACCURACY

public static final double SOLVER_DEFAULT_ABSOLUTE_ACCURACY

Default accuracy.

See Also:

Constant Field Values

randomData

@Deprecated
protected RandomDataImpl randomData

Deprecated. As of 3.1, to be removed in 4.0. Please use the random instance variable instead.

RandomData instance used to generate samples from the distribution.

random

protected final RandomGenerator random

RNG instance used to generate samples from the distribution.

Since:

3.1

Constructor Detail

AbstractRealDistribution

@Deprecated
protected AbstractRealDistribution()

Deprecated. As of 3.1, to be removed in 4.0. Please use AbstractRealDistribution(RandomGenerator) instead.

AbstractRealDistribution

protected AbstractRealDistribution(RandomGenerator rng)

Parameters:

rng - Random number generator.

Since:

3.1

Method Detail

cumulativeProbability

@Deprecated
public double cumulativeProbability(double x0,
                                               double x1)
                             throws NumberIsTooLargeException

Deprecated. As of 3.1 (to be removed in 4.0). Please use probability(double,double) instead.

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

P(x0 < X <= x1) = P(X <= x1) - P(X <= x0)

Specified by:

cumulativeProbability in interface RealDistribution

Parameters:

x0 - the exclusive lower bound

x1 - the inclusive upper bound

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

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).

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)
                                    throws OutOfRangeException

Computes the quantile function of this distribution. For a random variable X distributed according to this distribution, the returned value is

• inf{x in R | P(X<=x) >= p} for 0 < p <= 1,
• inf{x in R | P(X<=x) > 0} for p = 0.

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)

Throws:

OutOfRangeException - if p < 0 or p > 1

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