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java.lang.Objectorg.apache.commons.math3.distribution.AbstractIntegerDistribution
org.apache.commons.math3.distribution.EnumeratedIntegerDistribution
public class EnumeratedIntegerDistribution
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.
Field Summary | |
---|---|
protected EnumeratedDistribution<Integer> |
innerDistribution
EnumeratedDistribution instance (using the Integer wrapper)
used to generate the pmf. |
private static long |
serialVersionUID
Serializable UID. |
Fields inherited from class org.apache.commons.math3.distribution.AbstractIntegerDistribution |
---|
random, randomData |
Constructor Summary | |
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EnumeratedIntegerDistribution(int[] singletons,
double[] probabilities)
Create a discrete distribution using the given probability mass function definition. |
|
EnumeratedIntegerDistribution(RandomGenerator rng,
int[] singletons,
double[] probabilities)
Create a discrete distribution using the given random number generator and probability mass function definition. |
Method Summary | |
---|---|
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. |
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 org.apache.commons.math3.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 |
Field Detail |
---|
private static final long serialVersionUID
protected final EnumeratedDistribution<Integer> innerDistribution
EnumeratedDistribution
instance (using the Integer
wrapper)
used to generate the pmf.
Constructor Detail |
---|
public EnumeratedIntegerDistribution(int[] singletons, double[] probabilities) throws DimensionMismatchException, NotPositiveException, MathArithmeticException, NotFiniteNumberException, NotANumberException
singletons
- array of random variable values.probabilities
- array of probabilities.
DimensionMismatchException
- if
singletons.length != probabilities.length
NotPositiveException
- if any of the probabilities are negative.
NotFiniteNumberException
- if any of the probabilities are infinite.
NotANumberException
- if any of the probabilities are NaN.
MathArithmeticException
- all of the probabilities are 0.public EnumeratedIntegerDistribution(RandomGenerator rng, int[] singletons, double[] probabilities) throws DimensionMismatchException, NotPositiveException, MathArithmeticException, NotFiniteNumberException, NotANumberException
rng
- random number generator.singletons
- array of random variable values.probabilities
- array of probabilities.
DimensionMismatchException
- if
singletons.length != probabilities.length
NotPositiveException
- if any of the probabilities are negative.
NotFiniteNumberException
- if any of the probabilities are infinite.
NotANumberException
- if any of the probabilities are NaN.
MathArithmeticException
- all of the probabilities are 0.Method Detail |
---|
public 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 evaluated
x
public 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 evaluated
x
public 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()
true
public int sample()
sample
in interface IntegerDistribution
sample
in class AbstractIntegerDistribution
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