public interface IntegerDistribution
Modifier and Type  Interface and Description 

static interface 
IntegerDistribution.Sampler
Sampling functionality.

Modifier and Type  Method and Description 

IntegerDistribution.Sampler 
createSampler(org.apache.commons.rng.UniformRandomProvider rng)
Creates a sampler.

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.

int 
inverseCumulativeProbability(double p)
Computes the quantile function of this distribution.

boolean 
isSupportConnected()
Use this method to get information about whether the support is
connected, i.e.

double 
logProbability(int x)
For a random variable
X whose values are distributed according to
this distribution, this method returns log(P(X = x)) , where
log is the natural logarithm. 
double 
probability(int x)
For a random variable
X whose values are distributed according
to this distribution, this method returns P(X = x) . 
double 
probability(int x0,
int x1)
For a random variable
X whose values are distributed according
to this distribution, this method returns P(x0 < X <= x1) . 
double logProbability(int x)
X
whose values are distributed according to
this distribution, this method returns log(P(X = x))
, where
log
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 of
probability(int)
.x
 the point at which the PMF is evaluatedx
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 evaluatedx
double probability(int x0, int x1) throws NumberIsTooLargeException
X
whose values are distributed according
to this distribution, this method returns P(x0 < X <= x1)
.x0
 the exclusive lower boundx1
 the inclusive upper boundx0
and x1
,
excluding the lower and including the upper endpointNumberIsTooLargeException
 if x0 > x1
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 evaluatedx
int inverseCumulativeProbability(double p) throws OutOfRangeException
X
distributed according to this distribution,
the returned value is
inf{x in Z  P(X<=x) >= p}
for 0 < p <= 1
,inf{x in Z  P(X<=x) > 0}
for p = 0
.int
,
then Integer.MIN_VALUE
or Integer.MAX_VALUE
is returned.p
 the cumulative probabilityp
quantile of this distribution
(largest 0quantile for p = 0
)OutOfRangeException
 if p < 0
or p > 1
double getNumericalMean()
Double.NaN
if it is not defineddouble getNumericalVariance()
Double.POSITIVE_INFINITY
or
Double.NaN
if it is not defined)int getSupportLowerBound()
inverseCumulativeProbability(0)
. In other words, this
method must return
inf {x in Z  P(X <= x) > 0}
.
Integer.MIN_VALUE
for negative infinity)int getSupportUpperBound()
inverseCumulativeProbability(1)
. In other words, this
method must return
inf {x in R  P(X <= x) = 1}
.
Integer.MAX_VALUE
for positive infinity)boolean isSupportConnected()
IntegerDistribution.Sampler createSampler(org.apache.commons.rng.UniformRandomProvider rng)
rng
 Generator of uniformly distributed numbers.Copyright © 2003–2016 The Apache Software Foundation. All rights reserved.