public 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 and 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 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.
|
List<Pair<Integer,Double>> |
getPmf()
Return the probability mass function as a list of
|
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()
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