public class UniformRealDistribution extends AbstractRealDistribution
| Modifier and Type | Field and Description |
|---|---|
static double |
DEFAULT_INVERSE_ABSOLUTE_ACCURACY
Default inverse cumulative probability accuracy.
|
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)
Create a uniform distribution.
|
UniformRealDistribution(RandomGenerator rng,
double lower,
double upper,
double inverseCumAccuracy)
Creates a uniform distribution.
|
| 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.
|
protected double |
getSolverAbsoluteAccuracy()
Returns the solver absolute accuracy for inverse cumulative computation.
|
double |
getSupportLowerBound()
Access the lower bound of the support.
|
double |
getSupportUpperBound()
Access the upper bound of the support.
|
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, inverseCumulativeProbability, probability, probability, reseedRandomGenerator, samplepublic 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.public UniformRealDistribution(double lower,
double upper,
double inverseCumAccuracy)
throws NumberIsTooLargeException
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, double inverseCumAccuracy) throws NumberIsTooLargeException
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 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 evaluatedxpublic 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 evaluatedxprotected double getSolverAbsoluteAccuracy()
getSolverAbsoluteAccuracy in class AbstractRealDistributionpublic 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()
truepublic double sample()
sample in interface RealDistributionsample in class AbstractRealDistributionCopyright © 2003-2013 Apache Software Foundation. All Rights Reserved.