public class UniformIntegerDistribution extends AbstractIntegerDistribution
random, randomData| Constructor and Description | 
|---|
| UniformIntegerDistribution(int lower,
                          int upper)Creates a new uniform integer distribution using the given lower and
 upper bounds (both inclusive). | 
| UniformIntegerDistribution(RandomGenerator rng,
                          int lower,
                          int upper)Creates a new uniform integer distribution using the given lower and
 upper bounds (both inclusive). | 
| Modifier and Type | Method and Description | 
|---|---|
| double | cumulativeProbability(int x)For a random variable  Xwhose values are distributed according
 to this distribution, this method returnsP(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. | 
| boolean | isSupportConnected()Use this method to get information about whether the support is
 connected, i.e. | 
| double | probability(int x)For a random variable  Xwhose values are distributed according
 to this distribution, this method returnsP(X = x). | 
| int | sample()Generate a random value sampled from this distribution. | 
cumulativeProbability, inverseCumulativeProbability, logProbability, reseedRandomGenerator, sample, solveInverseCumulativeProbabilitypublic UniformIntegerDistribution(int lower,
                          int upper)
                           throws NumberIsTooLargeException
 Note: this constructor will implicitly create an instance of
 Well19937c as random generator to be used for sampling only (see
 sample() and AbstractIntegerDistribution.sample(int)). In case no sampling is
 needed for the created distribution, it is advised to pass null
 as random generator via the appropriate constructors to avoid the
 additional initialisation overhead.
lower - Lower bound (inclusive) of this distribution.upper - Upper bound (inclusive) of this distribution.NumberIsTooLargeException - if lower >= upper.public UniformIntegerDistribution(RandomGenerator rng, int lower, int upper) throws NumberIsTooLargeException
rng - Random number generator.lower - Lower bound (inclusive) of this distribution.upper - Upper bound (inclusive) of this distribution.NumberIsTooLargeException - if lower > upper.public 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 evaluatedxpublic 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 evaluatedxpublic 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, and
 n = upper - lower + 1, the variance is (n^2 - 1) / 12.Double.POSITIVE_INFINITY or
 Double.NaN if it is not defined)public int getSupportLowerBound()
inverseCumulativeProbability(0). In other words, this
 method must return
 inf {x in Z | P(X <= x) > 0}.
public int getSupportUpperBound()
inverseCumulativeProbability(1). In other words, this
 method must return
 inf {x in R | P(X <= x) = 1}.
public boolean isSupportConnected()
truepublic int sample()
sample in interface IntegerDistributionsample in class AbstractIntegerDistributionCopyright © 2003–2016 The Apache Software Foundation. All rights reserved.