fr.cnes.sirius.patrius.math.distribution

Class UniformIntegerDistribution

java.lang.Object

fr.cnes.sirius.patrius.math.distribution.AbstractIntegerDistribution

fr.cnes.sirius.patrius.math.distribution.UniformIntegerDistribution

All Implemented Interfaces:

IntegerDistribution, Serializable

public class UniformIntegerDistribution
extends AbstractIntegerDistribution

Implementation of the uniform integer distribution.

Since:

3.0

Version:

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

See Also:

Uniform distribution (discrete), at Wikipedia, Serialized Form

Field Summary

Fields inherited from class fr.cnes.sirius.patrius.math.distribution.AbstractIntegerDistribution

random

Constructor Summary

Constructors

Constructor and Description
UniformIntegerDistribution(int lowerIn, int upperIn) Creates a new uniform integer distribution using the given lower and upper bounds (both inclusive).
UniformIntegerDistribution(RandomGenerator rng, int lowerIn, int upperIn) Creates a new uniform integer distribution using the given lower and upper bounds (both inclusive).

Method Summary

Modifier and Type	Method and Description
double	cumulativeProbability(int x) For a random variable X whose values are distributed according to this distribution, this method returns P(X <= x).
double	getNumericalMean() Use this method to get the numerical value of the mean of this distribution.
double	getNumericalVariance() Use this method to get the numerical value of the variance of this distribution.
int	getSupportLowerBound() Access the lower bound of the support.
int	getSupportUpperBound() Access the upper bound of the support.
boolean	isSupportConnected() Use this method to get information about whether the support is connected, i.e. whether all integers between the lower and upper bound of the support are included in the support.
double	probability(int x) For a random variable X whose values are distributed according to this distribution, this method returns P(X = x).
int	sample() Generate a random value sampled from this distribution.

Methods inherited from class fr.cnes.sirius.patrius.math.distribution.AbstractIntegerDistribution

cumulativeProbability, inverseCumulativeProbability, reseedRandomGenerator, sample, solveInverseCumulativeProbability

Methods inherited from class java.lang.Object

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

Constructor Detail

UniformIntegerDistribution

public UniformIntegerDistribution(int lowerIn,
                                  int upperIn)

Creates a new uniform integer distribution using the given lower and upper bounds (both inclusive).

Parameters:

lowerIn - Lower bound (inclusive) of this distribution.

upperIn - Upper bound (inclusive) of this distribution.

Throws:

NumberIsTooLargeException - if lower >= upper.

UniformIntegerDistribution

public UniformIntegerDistribution(RandomGenerator rng,
                                  int lowerIn,
                                  int upperIn)

Creates a new uniform integer distribution using the given lower and upper bounds (both inclusive).

Parameters:

rng - Random number generator.

lowerIn - Lower bound (inclusive) of this distribution.

upperIn - Upper bound (inclusive) of this distribution.

Throws:

NumberIsTooLargeException - if lower >= upper.

Since:

3.1

Method Detail

probability

public double probability(int 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.

Parameters:

x - the point at which the PMF is evaluated

Returns:

the value of the probability mass function at x

cumulativeProbability

public double cumulativeProbability(int 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 (cumulative) distribution function (CDF) for this distribution.

Parameters:

x - the point at which the CDF is evaluated

Returns:

the probability that a random variable with this distribution takes a value less than or equal to x

getNumericalMean

public double getNumericalMean()

Use this method to get the numerical value of the mean of this distribution. For lower bound lower and upper bound upper, the mean is 0.5 * (lower + upper).

Returns:

the mean or Double.NaN if it is not defined

getNumericalVariance

public double getNumericalVariance()

Use this method to get the numerical value of the variance of this distribution. For lower bound lower and upper bound upper, and n = upper - lower + 1, the variance is (n^2 - 1) / 12.

Returns:

the variance (possibly Double.POSITIVE_INFINITY or Double.NaN if it is not defined)

getSupportLowerBound

public int getSupportLowerBound()

Access the lower bound of the support. This method must return the same value as inverseCumulativeProbability(0). In other words, this method must return

inf {x in Z | P(X <= x) > 0}.

The lower bound of the support is equal to the lower bound parameter of the distribution.

Returns:

lower bound of the support

getSupportUpperBound

public int getSupportUpperBound()

Access the upper bound of the support. This method must return the same value as inverseCumulativeProbability(1). In other words, this method must return

inf {x in R | P(X <= x) = 1}.

The upper bound of the support is equal to the upper bound parameter of the distribution.

Returns:

upper bound of the support

isSupportConnected

public boolean isSupportConnected()

Use this method to get information about whether the support is connected, i.e. whether all integers between the lower and upper bound of the support are included in the support. The support of this distribution is connected.

Returns:

true

sample

public int sample()

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

Specified by:

sample in interface IntegerDistribution

Overrides:

sample in class AbstractIntegerDistribution

Returns:

a random value