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## Uses of Interface
org.apache.commons.math3.random.RandomGenerator

Packages that use RandomGenerator
org.apache.commons.math3.distribution | Implementations of common discrete and continuous distributions.
org.apache.commons.math3.genetics | This package provides Genetic Algorithms components and implementations.
org.apache.commons.math3.optim.nonlinear.scalar.noderiv | This package provides optimization algorithms that do not require derivatives.
org.apache.commons.math3.optim.univariate | One-dimensional optimization algorithms.
org.apache.commons.math3.optimization.direct | This package provides optimization algorithms that don't require derivatives.
org.apache.commons.math3.optimization.univariate | Univariate real functions minimum finding algorithms.
org.apache.commons.math3.random | Random number and random data generators.
org.apache.commons.math3.stat.ranking | Classes providing rank transformations.

Uses of RandomGenerator in org.apache.commons.math3.distribution

Fields in org.apache.commons.math3.distribution declared as RandomGenerator
`protected RandomGenerator` | `AbstractMultivariateRealDistribution.random` RNG instance used to generate samples from the distribution.
`protected RandomGenerator` | `AbstractRealDistribution.random` RNG instance used to generate samples from the distribution.
`protected RandomGenerator` | `AbstractIntegerDistribution.random` RNG instance used to generate samples from the distribution.

Constructors in org.apache.commons.math3.distribution with parameters of type RandomGenerator
`AbstractIntegerDistribution(RandomGenerator rng)`
`AbstractMultivariateRealDistribution(RandomGenerator rng, int n)`
`AbstractRealDistribution(RandomGenerator rng)`
`BetaDistribution(RandomGenerator rng, double alpha, double beta, double inverseCumAccuracy)` Creates a β distribution.
`BinomialDistribution(RandomGenerator rng, int trials, double p)` Creates a binomial distribution.
`CauchyDistribution(RandomGenerator rng, double median, double scale, double inverseCumAccuracy)` Creates a Cauchy distribution.
`ChiSquaredDistribution(RandomGenerator rng, double degreesOfFreedom, double inverseCumAccuracy)` Create a Chi-Squared distribution with the given degrees of freedom and inverse cumulative probability accuracy.
`ExponentialDistribution(RandomGenerator rng, double mean, double inverseCumAccuracy)` Creates an exponential distribution.
`FDistribution(RandomGenerator rng, double numeratorDegreesOfFreedom, double denominatorDegreesOfFreedom, double inverseCumAccuracy)` Creates an F distribution.
`GammaDistribution(RandomGenerator rng, double shape, double scale, double inverseCumAccuracy)` Creates a Gamma distribution.
`HypergeometricDistribution(RandomGenerator rng, int populationSize, int numberOfSuccesses, int sampleSize)` Creates a new hypergeometric distribution.
`LogNormalDistribution(RandomGenerator rng, double scale, double shape, double inverseCumAccuracy)` Creates a log-normal distribution.
`MixtureMultivariateRealDistribution(RandomGenerator rng, List<Pair<Double,T>> components)` Creates a mixture model from a list of distributions and their associated weights.
`MultivariateNormalDistribution(RandomGenerator rng, double[] means, double[][] covariances)` Creates a multivariate normal distribution with the given mean vector and covariance matrix.
`NormalDistribution(RandomGenerator rng, double mean, double sd, double inverseCumAccuracy)` Creates a normal distribution.
`PascalDistribution(RandomGenerator rng, int r, double p)` Create a Pascal distribution with the given number of successes and probability of success.
`PoissonDistribution(RandomGenerator rng, double p, double epsilon, int maxIterations)` Creates a new Poisson distribution with specified mean, convergence criterion and maximum number of iterations.
`TDistribution(RandomGenerator rng, double degreesOfFreedom, double inverseCumAccuracy)` Creates a t distribution.
`TriangularDistribution(RandomGenerator rng, double a, double c, double b)` Creates a triangular distribution.
`UniformIntegerDistribution(RandomGenerator rng, int lower, int upper)` Creates a new uniform integer distribution using the given lower and upper bounds (both inclusive).
`UniformRealDistribution(RandomGenerator rng, double lower, double upper, double inverseCumAccuracy)` Creates a uniform distribution.
`WeibullDistribution(RandomGenerator rng, double alpha, double beta, double inverseCumAccuracy)` Creates a Weibull distribution.
`ZipfDistribution(RandomGenerator rng, int numberOfElements, double exponent)` Creates a Zipf distribution.

Uses of RandomGenerator in org.apache.commons.math3.genetics

Methods in org.apache.commons.math3.genetics that return RandomGenerator
`static RandomGenerator` | `GeneticAlgorithm.getRandomGenerator()` Returns the (static) random generator.

Methods in org.apache.commons.math3.genetics with parameters of type RandomGenerator
`static void` | `GeneticAlgorithm.setRandomGenerator(RandomGenerator random)` Set the (static) random generator.

Uses of RandomGenerator in org.apache.commons.math3.optim.nonlinear.scalar.noderiv

Constructors in org.apache.commons.math3.optim.nonlinear.scalar.noderiv with parameters of type RandomGenerator
`CMAESOptimizer(int maxIterations, double stopFitness, boolean isActiveCMA, int diagonalOnly, int checkFeasableCount, RandomGenerator random, boolean generateStatistics, ConvergenceChecker<PointValuePair> checker)`

Uses of RandomGenerator in org.apache.commons.math3.optim.univariate

Constructors in org.apache.commons.math3.optim.univariate with parameters of type RandomGenerator
`MultiStartUnivariateOptimizer(UnivariateOptimizer optimizer, int starts, RandomGenerator generator)` Create a multi-start optimizer from a single-start optimizer.

Uses of RandomGenerator in org.apache.commons.math3.optimization.direct

Fields in org.apache.commons.math3.optimization.direct declared as RandomGenerator
`static RandomGenerator` | `CMAESOptimizer.DEFAULT_RANDOMGENERATOR` Deprecated. Default value for `CMAESOptimizer.random`.

Constructors in org.apache.commons.math3.optimization.direct with parameters of type RandomGenerator
`CMAESOptimizer(int lambda, double[] inputSigma, int maxIterations, double stopFitness, boolean isActiveCMA, int diagonalOnly, int checkFeasableCount, RandomGenerator random, boolean generateStatistics)` Deprecated. See `SimpleValueChecker.SimpleValueChecker()`
`CMAESOptimizer(int lambda, double[] inputSigma, int maxIterations, double stopFitness, boolean isActiveCMA, int diagonalOnly, int checkFeasableCount, RandomGenerator random, boolean generateStatistics, ConvergenceChecker<PointValuePair> checker)` Deprecated. As of version 3.1: Parameters `lambda` and `inputSigma` must be passed with the call to `optimize`.
`CMAESOptimizer(int maxIterations, double stopFitness, boolean isActiveCMA, int diagonalOnly, int checkFeasableCount, RandomGenerator random, boolean generateStatistics, ConvergenceChecker<PointValuePair> checker)` Deprecated.

Uses of RandomGenerator in org.apache.commons.math3.optimization.univariate

Constructors in org.apache.commons.math3.optimization.univariate with parameters of type RandomGenerator
`UnivariateMultiStartOptimizer(BaseUnivariateOptimizer<FUNC> optimizer, int starts, RandomGenerator generator)` Deprecated. Create a multi-start optimizer from a single-start optimizer.

Uses of RandomGenerator in org.apache.commons.math3.random

Classes in org.apache.commons.math3.random that implement RandomGenerator
`class` | `AbstractRandomGenerator` Abstract class implementing the `RandomGenerator` interface.
`class` | `AbstractWell` This abstract class implements the WELL class of pseudo-random number generator from François Panneton, Pierre L'Ecuyer and Makoto Matsumoto.
`class` | `BitsStreamGenerator` Base class for random number generators that generates bits streams.
`class` | `ISAACRandom` ISAAC: a fast cryptographic pseudo-random number generator ISAAC (Indirection, Shift, Accumulate, Add, and Count) generates 32-bit random numbers.
`class` | `JDKRandomGenerator` Extension of `java.util.Random` to implement `RandomGenerator`.
`class` | `MersenneTwister` This class implements a powerful pseudo-random number generator developed by Makoto Matsumoto and Takuji Nishimura during 1996-1997.
`class` | `RandomAdaptor` Extension of `java.util.Random` wrapping a `RandomGenerator`.
`class` | `SynchronizedRandomGenerator` Any `RandomGenerator` implementation can be thread-safe if it is used through an instance of this class.
`class` | `Well1024a` This class implements the WELL1024a pseudo-random number generator from François Panneton, Pierre L'Ecuyer and Makoto Matsumoto.
`class` | `Well19937a` This class implements the WELL19937a pseudo-random number generator from François Panneton, Pierre L'Ecuyer and Makoto Matsumoto.
`class` | `Well19937c` This class implements the WELL19937c pseudo-random number generator from François Panneton, Pierre L'Ecuyer and Makoto Matsumoto.
`class` | `Well44497a` This class implements the WELL44497a pseudo-random number generator from François Panneton, Pierre L'Ecuyer and Makoto Matsumoto.
`class` | `Well44497b` This class implements the WELL44497b pseudo-random number generator from François Panneton, Pierre L'Ecuyer and Makoto Matsumoto.
`class` | `Well512a` This class implements the WELL512a pseudo-random number generator from François Panneton, Pierre L'Ecuyer and Makoto Matsumoto.

Methods in org.apache.commons.math3.random with parameters of type RandomGenerator
`static Random` | `RandomAdaptor.createAdaptor(RandomGenerator randomGenerator)` Factory method to create a `Random` using the supplied `RandomGenerator`.

Constructors in org.apache.commons.math3.random with parameters of type RandomGenerator
`EmpiricalDistribution(int binCount, RandomGenerator generator)` Creates a new EmpiricalDistribution with the specified bin count using the provided `RandomGenerator` as the source of random data.
`EmpiricalDistribution(RandomGenerator generator)` Creates a new EmpiricalDistribution with default bin count using the provided `RandomGenerator` as the source of random data.
`GaussianRandomGenerator(RandomGenerator generator)` Create a new generator.
`RandomAdaptor(RandomGenerator randomGenerator)` Construct a RandomAdaptor wrapping the supplied RandomGenerator.
`RandomDataGenerator(RandomGenerator rand)` Construct a RandomDataGenerator using the supplied `RandomGenerator` as the source of (non-secure) random data.
`RandomDataImpl(RandomGenerator rand)` Deprecated. Construct a RandomDataImpl using the supplied `RandomGenerator` as the source of (non-secure) random data.
`StableRandomGenerator(RandomGenerator generator, double alpha, double beta)` Create a new generator.
`SynchronizedRandomGenerator(RandomGenerator rng)` Creates a synchronized wrapper for the given `RandomGenerator` instance.
`UniformRandomGenerator(RandomGenerator generator)` Create a new generator.
`UnitSphereRandomVectorGenerator(int dimension, RandomGenerator rand)`
`ValueServer(RandomGenerator generator)` Construct a ValueServer instance using a RandomGenerator as its source of random data.

Uses of RandomGenerator in org.apache.commons.math3.stat.ranking

Constructors in org.apache.commons.math3.stat.ranking with parameters of type RandomGenerator
`NaturalRanking(NaNStrategy nanStrategy, RandomGenerator randomGenerator)` Create a NaturalRanking with the given NaNStrategy, TiesStrategy.RANDOM and the given source of random data.
`NaturalRanking(RandomGenerator randomGenerator)` Create a NaturalRanking with TiesStrategy.RANDOM and the given RandomGenerator as the source of random data.

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