public interface RealDistribution
Modifier and Type  Interface and Description 

static interface 
RealDistribution.Sampler
Sampling functionality.

Modifier and Type  Method and Description 

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

double 
cumulativeProbability(double x)
For a random variable
X whose values are distributed according
to this distribution, this method returns P(X <= x) . 
double 
density(double x)
Returns the probability density function (PDF) of this distribution
evaluated at the specified point
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.

double 
getSupportLowerBound()
Access the lower bound of the support.

double 
getSupportUpperBound()
Access the upper bound of the support.

double 
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 
logDensity(double x)
Returns the natural logarithm of the probability density function
(PDF) of this distribution evaluated at the specified point
x . 
double 
probability(double x)
For a random variable
X whose values are distributed according
to this distribution, this method returns P(X = x) . 
double 
probability(double x0,
double x1)
For a random variable
X whose values are distributed according
to this distribution, this method returns P(x0 < X <= x1) . 
double probability(double 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(double x0, double 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 density(double x)
x
. In general, the PDF is
the derivative of the CDF
.
If the derivative does not exist at x
, then an appropriate
replacement should be returned, e.g. Double.POSITIVE_INFINITY
,
Double.NaN
, or the limit inferior or limit superior of the
difference quotient.x
 the point at which the PDF is evaluatedx
double logDensity(double x)
x
.
In general, the PDF is the derivative of the CDF
.
If the derivative does not exist at x
, then an appropriate replacement
should be returned, e.g. Double.POSITIVE_INFINITY
, Double.NaN
,
or the limit inferior or limit superior of the difference quotient. 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
density(double)
.x
 the point at which the PDF is evaluatedx
double cumulativeProbability(double 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
double inverseCumulativeProbability(double p) throws OutOfRangeException
X
distributed according to this distribution, the
returned value is
inf{x in R  P(X<=x) >= p}
for 0 < p <= 1
,inf{x in R  P(X<=x) > 0}
for p = 0
.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
as
for certain cases in TDistribution
) or Double.NaN
if it
is not defineddouble getSupportLowerBound()
inverseCumulativeProbability(0)
. In other words, this
method must return
inf {x in R  P(X <= x) > 0}
.
Double.NEGATIVE_INFINITY
)double getSupportUpperBound()
inverseCumulativeProbability(1)
. In other words, this
method must return
inf {x in R  P(X <= x) = 1}
.
Double.POSITIVE_INFINITY
)boolean isSupportConnected()
RealDistribution.Sampler createSampler(org.apache.commons.rng.UniformRandomProvider rng)
rng
 Generator of uniformly distributed numbers.Copyright © 2003–2016 The Apache Software Foundation. All rights reserved.