Class EnumeratedRealDistribution
java.lang.Object
org.hipparchus.distribution.continuous.AbstractRealDistribution
org.hipparchus.distribution.continuous.EnumeratedRealDistribution
 All Implemented Interfaces:
Serializable
,RealDistribution
Implementation of a realvalued
EnumeratedDistribution
.
Values with zeroprobability 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:

Field Summary
Fields inherited from class org.hipparchus.distribution.continuous.AbstractRealDistribution
DEFAULT_SOLVER_ABSOLUTE_ACCURACY

Constructor Summary
ConstructorDescriptionEnumeratedRealDistribution
(double[] data) Create a discrete realvalued distribution from the input data.EnumeratedRealDistribution
(double[] singletons, double[] probabilities) Create a discrete realvalued distribution using the given probability mass function enumeration. 
Method Summary
Modifier and TypeMethodDescriptiondouble
cumulativeProbability
(double x) For a random variableX
whose values are distributed according to this distribution, this method returnsP(X <= x)
.double
density
(double x) For a random variableX
whose values are distributed according to this distribution, this method returnsP(X = x)
.double
Use this method to get the numerical value of the mean of this distribution.double
Use this method to get the numerical value of the variance of this distribution.getPmf()
Return the probability mass function as a list of (value, probability) pairs.double
Access the lower bound of the support.double
Access the upper bound of the support.double
inverseCumulativeProbability
(double p) Computes the quantile function of this distribution.boolean
Use this method to get information about whether the support is connected, i.e.double
probability
(double x) For a random variableX
whose values are distributed according to this distribution, this method returnsP(X = x)
.Methods inherited from class org.hipparchus.distribution.continuous.AbstractRealDistribution
getSolverAbsoluteAccuracy, logDensity, probability

Constructor Details

EnumeratedRealDistribution
public EnumeratedRealDistribution(double[] data) Create a discrete realvalued 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

EnumeratedRealDistribution
public EnumeratedRealDistribution(double[] singletons, double[] probabilities) throws MathIllegalArgumentException Create a discrete realvalued distribution using the given probability mass function enumeration. Parameters:
singletons
 array of random variable values.probabilities
 array of probabilities. Throws:
MathIllegalArgumentException
 ifsingletons.length != probabilities.length
MathIllegalArgumentException
 if any of the probabilities are negative.MathIllegalArgumentException
 if any of the probabilities are NaN.MathIllegalArgumentException
 if any of the probabilities are infinite.


Method Details

probability
public double probability(double x) For a random variableX
whose values are distributed according to this distribution, this method returnsP(X = x)
. In other words, this method represents the probability mass function (PMF) for the distribution.Note that if
x1
andx2
satisfyx1.equals(x2)
, or both are null, thenprobability(x1) = probability(x2)
. Parameters:
x
 the point at which the PMF is evaluated Returns:
 the value of the probability mass function at
x

density
public double density(double x) For a random variableX
whose values are distributed according to this distribution, this method returnsP(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 variableX
whose values are distributed according to this distribution, this method returnsP(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

inverseCumulativeProbability
Computes the quantile function of this distribution. For a random variableX
distributed according to this distribution, the returned value isinf{x in R  P(X<=x) >= p}
for0 < p <= 1
,inf{x in R  P(X<=x) > 0}
forp = 0
.
RealDistribution.getSupportLowerBound()
forp = 0
,RealDistribution.getSupportUpperBound()
forp = 1
.
 Specified by:
inverseCumulativeProbability
in interfaceRealDistribution
 Overrides:
inverseCumulativeProbability
in classAbstractRealDistribution
 Parameters:
p
 the cumulative probability Returns:
 the smallest
p
quantile of this distribution (largest 0quantile forp = 0
)  Throws:
MathIllegalArgumentException
 ifp < 0
orp > 1

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 asinverseCumulativeProbability(0)
. In other words, this method must return
Returns the lowest value with nonzero probability.inf {x in R  P(X <= x) > 0}
. Returns:
 the lowest value with nonzero probability.

getSupportUpperBound
public double getSupportUpperBound()Access the upper bound of the support. This method must return the same value asinverseCumulativeProbability(1)
. In other words, this method must return
Returns the highest value with nonzero probability.inf {x in R  P(X <= x) = 1}
. Returns:
 the highest value with nonzero probability.

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

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