Package org.hipparchus.distribution.discrete

Class EnumeratedIntegerDistribution

java.lang.Object

org.hipparchus.distribution.discrete.AbstractIntegerDistribution

org.hipparchus.distribution.discrete.EnumeratedIntegerDistribution

All Implemented Interfaces:

Serializable, IntegerDistribution

public class EnumeratedIntegerDistribution
extends AbstractIntegerDistribution

Implementation of an integer-valued EnumeratedDistribution.

Values with zero-probability are allowed but they do not extend the support.

Duplicate values are allowed. Probabilities of duplicate values are combined when computing cumulative probabilities and statistics.

See Also:

Serialized Form

Constructor Summary

Constructors

Constructor	Description
EnumeratedIntegerDistribution(int[] data)	Create a discrete integer-valued distribution from the input data.
EnumeratedIntegerDistribution(int[] singletons, double[] probabilities)	Create a discrete distribution using the given probability mass function definition.

Method Summary

Modifier and Type	Method	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.
List<Pair<Integer,Double>>	getPmf()	Return the probability mass function as a list of (value, probability) pairs.
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).

Methods inherited from class org.hipparchus.distribution.discrete.AbstractIntegerDistribution

inverseCumulativeProbability, logProbability, probability, solveInverseCumulativeProbability

Methods inherited from class java.lang.Object

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

Constructor Detail

EnumeratedIntegerDistribution

public EnumeratedIntegerDistribution(int[] singletons,
                                     double[] probabilities)
                              throws MathIllegalArgumentException

Create a discrete distribution using the given probability mass function definition.

Parameters:

singletons - array of random variable values.

probabilities - array of probabilities.

Throws:

MathIllegalArgumentException - if singletons.length != probabilities.length

MathIllegalArgumentException - if probabilities contains negative, infinite or NaN values or only 0's

EnumeratedIntegerDistribution

public EnumeratedIntegerDistribution(int[] data)

Create a discrete integer-valued distribution from the input data. Values are assigned mass based on their frequency. For example, [0,1,1,2] as input creates a distribution with values 0, 1 and 2 having probability masses 0.25, 0.5 and 0.25 respectively,

Parameters:

data - input dataset

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.

Returns:

sum(singletons[i] * probabilities[i])

getNumericalVariance

public double getNumericalVariance()

Use this method to get the numerical value of the variance of this distribution.

Returns:

sum((singletons[i] - mean) ^ 2 * probabilities[i])

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}.

Returns the lowest value with non-zero probability.

Returns:

the lowest value with non-zero probability.

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}.

Returns the highest value with non-zero probability.

Returns:

the highest value with non-zero probability.

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

getPmf

public List<Pair<Integer,Double>> getPmf()

Return the probability mass function as a list of (value, probability) pairs.

Returns:

the probability mass function.