EnumeratedRealDistribution
org.apache.commons.math3.distribution

## Class EnumeratedRealDistribution

• ### Constructor Summary

Constructors
Constructor and Description
EnumeratedRealDistribution(double[] singletons, double[] probabilities)
Create a discrete distribution using the given probability mass function enumeration.
EnumeratedRealDistribution(RandomGenerator rng, double[] singletons, double[] probabilities)
Create a discrete distribution using the given random number generator and probability mass function enumeration.
• ### Method Detail

• #### 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
Overrides:
probability in class AbstractRealDistribution
Parameters:
x - the point at which the PMF is evaluated
Returns:
zero.
• #### density

public double density(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.
Parameters:
x - the point at which the PMF is evaluated
Returns:
the value of the probability mass function at point x
• #### cumulativeProbability

public double cumulativeProbability(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 (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 double 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 R | P(X <= x) > 0}.

Returns the lowest value with non-zero probability.
Returns:
the lowest value with non-zero probability.
• #### getSupportUpperBound

public double 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.
• #### isSupportLowerBoundInclusive

public boolean isSupportLowerBoundInclusive()
Whether or not the lower bound of support is in the domain of the density function. Returns true iff getSupporLowerBound() is finite and density(getSupportLowerBound()) returns a non-NaN, non-infinite value. The support of this distribution includes the lower bound.
Returns:
true
• #### isSupportUpperBoundInclusive

public boolean isSupportUpperBoundInclusive()
Whether or not the upper bound of support is in the domain of the density function. Returns true iff getSupportUpperBound() is finite and density(getSupportUpperBound()) returns a non-NaN, non-infinite value. The support of this distribution includes the upper bound.
Returns:
true
• #### isSupportConnected

public boolean isSupportConnected()
Use this method to get information about whether the support is connected, i.e. whether all values between the lower and upper bound of the support are included in the support. The support of this distribution is connected.
Returns:
true