public class UniformRealDistribution extends AbstractRealDistribution
Modifier and Type | Field and Description |
---|---|
static double |
DEFAULT_INVERSE_ABSOLUTE_ACCURACY
Deprecated.
as of 3.2 not used anymore, will be removed in 4.0
|
random, randomData, SOLVER_DEFAULT_ABSOLUTE_ACCURACY
Constructor and Description |
---|
UniformRealDistribution()
Create a standard uniform real distribution with lower bound (inclusive)
equal to zero and upper bound (exclusive) equal to one.
|
UniformRealDistribution(double lower,
double upper)
Create a uniform real distribution using the given lower and upper
bounds.
|
UniformRealDistribution(double lower,
double upper,
double inverseCumAccuracy)
Deprecated.
as of 3.2, inverse CDF is now calculated analytically, use
UniformRealDistribution(double, double) instead. |
UniformRealDistribution(RandomGenerator rng,
double lower,
double upper)
Creates a uniform distribution.
|
UniformRealDistribution(RandomGenerator rng,
double lower,
double upper,
double inverseCumAccuracy)
Deprecated.
as of 3.2, inverse CDF is now calculated analytically, use
UniformRealDistribution(RandomGenerator, double, double)
instead. |
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)
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.
|
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 |
sample()
Generate a random value sampled from this distribution.
|
cumulativeProbability, getSolverAbsoluteAccuracy, logDensity, probability, probability, reseedRandomGenerator, sample
@Deprecated public static final double DEFAULT_INVERSE_ABSOLUTE_ACCURACY
public UniformRealDistribution()
public UniformRealDistribution(double lower, double upper) throws NumberIsTooLargeException
lower
- Lower bound of this distribution (inclusive).upper
- Upper bound of this distribution (exclusive).NumberIsTooLargeException
- if lower >= upper
.@Deprecated public UniformRealDistribution(double lower, double upper, double inverseCumAccuracy) throws NumberIsTooLargeException
UniformRealDistribution(double, double)
instead.lower
- Lower bound of this distribution (inclusive).upper
- Upper bound of this distribution (exclusive).inverseCumAccuracy
- Inverse cumulative probability accuracy.NumberIsTooLargeException
- if lower >= upper
.@Deprecated public UniformRealDistribution(RandomGenerator rng, double lower, double upper, double inverseCumAccuracy)
UniformRealDistribution(RandomGenerator, double, double)
instead.rng
- Random number generator.lower
- Lower bound of this distribution (inclusive).upper
- Upper bound of this distribution (exclusive).inverseCumAccuracy
- Inverse cumulative probability accuracy.NumberIsTooLargeException
- if lower >= upper
.public UniformRealDistribution(RandomGenerator rng, double lower, double upper) throws NumberIsTooLargeException
rng
- Random number generator.lower
- Lower bound of this distribution (inclusive).upper
- Upper bound of this distribution (exclusive).NumberIsTooLargeException
- if lower >= upper
.public 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
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
AbstractRealDistribution
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()
lower
and upper bound upper
, the mean is
0.5 * (lower + upper)
.Double.NaN
if it is not definedpublic double getNumericalVariance()
lower
and upper bound upper
, the
variance is (upper - lower)^2 / 12
.Double.POSITIVE_INFINITY
as
for certain cases in TDistribution
) or Double.NaN
if it
is not definedpublic 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.public boolean isSupportUpperBoundInclusive()
getSupportUpperBound()
is finite and
density(getSupportUpperBound())
returns a non-NaN, non-infinite
value.public boolean isSupportConnected()
true
public double sample()
sample
in interface RealDistribution
sample
in class AbstractRealDistribution
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