public class EnumeratedRealDistribution extends AbstractRealDistribution
Implementation of a real-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.
Modifier and Type | Field and Description |
---|---|
protected EnumeratedDistribution<Double> |
innerDistribution
EnumeratedDistribution (using the Double wrapper)
used to generate the pmf. |
random, randomData, SOLVER_DEFAULT_ABSOLUTE_ACCURACY
Constructor and Description |
---|
EnumeratedRealDistribution(double[] singletons,
double[] probabilities)
Create a discrete distribution using the given probability mass function
enumeration.
|
EnumeratedRealDistribution(RandomGenerator rng,
double[] singletons,
double[] probabilities)
Create a discrete distribution using the given random number generator
and probability mass function enumeration.
|
Modifier and Type | Method and Description |
---|---|
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)
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.
|
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.
|
boolean |
isSupportLowerBoundInclusive()
Whether or not the lower bound of support is in the domain of the density
function.
|
boolean |
isSupportUpperBoundInclusive()
Whether or not the upper bound of support is in the domain of the density
function.
|
double |
probability(double x)
For a random variable
X whose values are distributed according
to this distribution, this method returns P(X = x) . |
double |
sample()
Generate a random value sampled from this distribution.
|
cumulativeProbability, getSolverAbsoluteAccuracy, logDensity, probability, reseedRandomGenerator, sample
protected final EnumeratedDistribution<Double> innerDistribution
EnumeratedDistribution
(using the Double
wrapper)
used to generate the pmf.public EnumeratedRealDistribution(double[] 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 EnumeratedRealDistribution(RandomGenerator rng, double[] 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.public 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.probability
in interface RealDistribution
probability
in class AbstractRealDistribution
x
- the point at which the PMF is evaluatedpublic double density(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
public 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
public 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
.RealDistribution.getSupportLowerBound()
for p = 0
,RealDistribution.getSupportUpperBound()
for p = 1
.inverseCumulativeProbability
in interface RealDistribution
inverseCumulativeProbability
in class AbstractRealDistribution
p
- the cumulative probabilityp
-quantile of this distribution
(largest 0-quantile for p = 0
)OutOfRangeException
- if p < 0
or p > 1
public double getNumericalMean()
sum(singletons[i] * probabilities[i])
public double getNumericalVariance()
sum((singletons[i] - mean) ^ 2 * probabilities[i])
public double getSupportLowerBound()
inverseCumulativeProbability(0)
. In other words, this
method must return
inf {x in R | P(X <= x) > 0}
.
public double getSupportUpperBound()
inverseCumulativeProbability(1)
. In other words, this
method must return
inf {x in R | P(X <= x) = 1}
.
public boolean isSupportLowerBoundInclusive()
getSupporLowerBound()
is finite and
density(getSupportLowerBound())
returns a non-NaN, non-infinite
value.
The support of this distribution includes the lower bound.true
public boolean isSupportUpperBoundInclusive()
getSupportUpperBound()
is finite and
density(getSupportUpperBound())
returns a non-NaN, non-infinite
value.
The support of this distribution includes the upper bound.true
public boolean isSupportConnected()
true
public double sample()
sample
in interface RealDistribution
sample
in class AbstractRealDistribution
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