Serializable, IntegerDistributionpublic class EnumeratedIntegerDistribution extends AbstractIntegerDistribution
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.
| 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. 
 | 
| 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. 
 | 
double | 
probability(int x) | 
 For a random variable  
X whose values are distributed according
 to this distribution, this method returns P(X = x). | 
inverseCumulativeProbability, logProbability, probability, solveInverseCumulativeProbabilitypublic EnumeratedIntegerDistribution(int[] singletons,
                                     double[] probabilities)
                              throws MathIllegalArgumentException
singletons - array of random variable values.probabilities - array of probabilities.MathIllegalArgumentException - if
 singletons.length != probabilities.lengthMathIllegalArgumentException - if probabilities contains negative, infinite or NaN values or only 0'spublic EnumeratedIntegerDistribution(int[] data)
data - input datasetpublic double probability(int x)
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.x - the point at which the PMF is evaluatedxpublic double cumulativeProbability(int x)
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.x - the point at which the CDF is evaluatedxpublic double getNumericalMean()
sum(singletons[i] * probabilities[i])public double getNumericalVariance()
sum((singletons[i] - mean) ^ 2 * probabilities[i])public int getSupportLowerBound()
inverseCumulativeProbability(0). In other words, this
 method must return
 inf {x in Z | P(X <= x) > 0}.
public int getSupportUpperBound()
inverseCumulativeProbability(1). In other words, this
 method must return
 inf {x in R | P(X <= x) = 1}.
public boolean isSupportConnected()
trueCopyright © 2016–2018 Hipparchus.org. All rights reserved.