Class GeometricDistribution
java.lang.Object
org.hipparchus.distribution.discrete.AbstractIntegerDistribution
org.hipparchus.distribution.discrete.GeometricDistribution
 All Implemented Interfaces:
Serializable
,IntegerDistribution
Implementation of the geometric distribution.

Constructor Summary
ConstructorDescriptionGeometricDistribution
(double p) Create a geometric distribution with the given probability of success. 
Method Summary
Modifier and TypeMethodDescriptiondouble
cumulativeProbability
(int 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.double
Access the probability of success for this distribution.int
Access the lower bound of the support.int
Access the upper bound of the support.int
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
logProbability
(int x) For a random variableX
whose values are distributed according to this distribution, this method returnslog(P(X = x))
, wherelog
is the natural logarithm.double
probability
(int 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.discrete.AbstractIntegerDistribution
probability, solveInverseCumulativeProbability

Constructor Details

GeometricDistribution
Create a geometric distribution with the given probability of success. Parameters:
p
 probability of success. Throws:
MathIllegalArgumentException
 ifp <= 0
orp > 1
.


Method Details

getProbabilityOfSuccess
public double getProbabilityOfSuccess()Access the probability of success for this distribution. Returns:
 the probability of success.

probability
public double probability(int 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
x

logProbability
public double logProbability(int x) For a random variableX
whose values are distributed according to this distribution, this method returnslog(P(X = x))
, wherelog
is the natural logarithm. In other words, this method represents the logarithm of the probability mass function (PMF) for the distribution. Note that due to the floating point precision and under/overflow issues, this method will for some distributions be more precise and faster than computing the logarithm ofIntegerDistribution.probability(int)
.The default implementation simply computes the logarithm of
probability(x)
. Specified by:
logProbability
in interfaceIntegerDistribution
 Overrides:
logProbability
in classAbstractIntegerDistribution
 Parameters:
x
 the point at which the PMF is evaluated Returns:
 the logarithm of the value of the probability mass function at
x

cumulativeProbability
public double cumulativeProbability(int 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

getNumericalMean
public double getNumericalMean()Use this method to get the numerical value of the mean of this distribution. For probability parameterp
, the mean is(1  p) / p
. Returns:
 the mean or
Double.NaN
if it is not defined

getNumericalVariance
public double getNumericalVariance()Use this method to get the numerical value of the variance of this distribution. For probability parameterp
, the variance is(1  p) / (p * p)
. Returns:
 the variance (possibly
Double.POSITIVE_INFINITY
orDouble.NaN
if it is not defined)

getSupportLowerBound
public int getSupportLowerBound()Access the lower bound of the support. This method must return the same value asinverseCumulativeProbability(0)
. In other words, this method must return
The lower bound of the support is always 0.inf {x in Z  P(X <= x) > 0}
. Returns:
 lower bound of the support (always 0)

getSupportUpperBound
public int getSupportUpperBound()Access the upper bound of the support. This method must return the same value asinverseCumulativeProbability(1)
. In other words, this method must return
The upper bound of the support is infinite (which we approximate asinf {x in R  P(X <= x) = 1}
.Integer.MAX_VALUE
). Returns:
 upper bound of the support (always Integer.MAX_VALUE)

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

inverseCumulativeProbability
Computes the quantile function of this distribution. For a random variableX
distributed according to this distribution, the returned value isinf{x in Z  P(X<=x) >= p}
for0 < p <= 1
,inf{x in Z  P(X<=x) > 0}
forp = 0
.
int
, thenInteger.MIN_VALUE
orInteger.MAX_VALUE
is returned. The default implementation returnsIntegerDistribution.getSupportLowerBound()
forp = 0
,IntegerDistribution.getSupportUpperBound()
forp = 1
, andAbstractIntegerDistribution.solveInverseCumulativeProbability(double, int, int)
for0 < p < 1
.
 Specified by:
inverseCumulativeProbability
in interfaceIntegerDistribution
 Overrides:
inverseCumulativeProbability
in classAbstractIntegerDistribution
 Parameters:
p
 the cumulative probability Returns:
 the smallest
p
quantile of this distribution (largest 0quantile forp = 0
)  Throws:
MathIllegalArgumentException
 ifp < 0
orp > 1
