| Package | Description | 
|---|---|
| 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.ml.clustering | Clustering algorithms. | 
| org.apache.commons.math3.ml.neuralnet | Neural networks. | 
| 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.inference | Classes providing hypothesis testing. | 
| org.apache.commons.math3.stat.ranking | Classes providing rank transformations. | 
| org.apache.commons.math3.util | Convenience routines and common data structures used throughout the commons-math library. | 
| Modifier and Type | Field and Description | 
|---|---|
| protected RandomGenerator | EnumeratedDistribution. randomRNG instance used to generate samples from the distribution. | 
| protected RandomGenerator | AbstractMultivariateRealDistribution. randomRNG instance used to generate samples from the distribution. | 
| protected RandomGenerator | AbstractRealDistribution. randomRNG instance used to generate samples from the distribution. | 
| protected RandomGenerator | AbstractIntegerDistribution. randomRNG instance used to generate samples from the distribution. | 
| Constructor and Description | 
|---|
| AbstractIntegerDistribution(RandomGenerator rng) | 
| AbstractMultivariateRealDistribution(RandomGenerator rng,
                                    int n) | 
| AbstractRealDistribution(RandomGenerator rng) | 
| BetaDistribution(RandomGenerator rng,
                double alpha,
                double beta)Creates a β distribution. | 
| 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)Creates a Cauchy distribution. | 
| CauchyDistribution(RandomGenerator rng,
                  double median,
                  double scale,
                  double inverseCumAccuracy)Creates a Cauchy distribution. | 
| ChiSquaredDistribution(RandomGenerator rng,
                      double degreesOfFreedom)Create a Chi-Squared distribution with the given degrees of freedom. | 
| ChiSquaredDistribution(RandomGenerator rng,
                      double degreesOfFreedom,
                      double inverseCumAccuracy)Create a Chi-Squared distribution with the given degrees of freedom and
 inverse cumulative probability accuracy. | 
| EnumeratedDistribution(RandomGenerator rng,
                      List<Pair<T,Double>> pmf)Create an enumerated distribution using the given random number generator
 and probability mass function enumeration. | 
| EnumeratedIntegerDistribution(RandomGenerator rng,
                             int[] data)Create a discrete integer-valued distribution from the input data. | 
| EnumeratedIntegerDistribution(RandomGenerator rng,
                             int[] singletons,
                             double[] probabilities)Create a discrete distribution using the given random number generator
 and probability mass function definition. | 
| EnumeratedRealDistribution(RandomGenerator rng,
                          double[] data)Create a discrete real-valued distribution from the input data. | 
| EnumeratedRealDistribution(RandomGenerator rng,
                          double[] singletons,
                          double[] probabilities)Create a discrete real-valued distribution using the given random number generator
 and probability mass function enumeration. | 
| ExponentialDistribution(RandomGenerator rng,
                       double mean)Creates an exponential distribution. | 
| ExponentialDistribution(RandomGenerator rng,
                       double mean,
                       double inverseCumAccuracy)Creates an exponential distribution. | 
| FDistribution(RandomGenerator rng,
             double numeratorDegreesOfFreedom,
             double denominatorDegreesOfFreedom)Creates an F distribution. | 
| FDistribution(RandomGenerator rng,
             double numeratorDegreesOfFreedom,
             double denominatorDegreesOfFreedom,
             double inverseCumAccuracy)Creates an F distribution. | 
| GammaDistribution(RandomGenerator rng,
                 double shape,
                 double scale)Creates a Gamma distribution. | 
| GammaDistribution(RandomGenerator rng,
                 double shape,
                 double scale,
                 double inverseCumAccuracy)Creates a Gamma distribution. | 
| GeometricDistribution(RandomGenerator rng,
                     double p)Creates a geometric distribution. | 
| GumbelDistribution(RandomGenerator rng,
                  double mu,
                  double beta)Build a new instance. | 
| HypergeometricDistribution(RandomGenerator rng,
                          int populationSize,
                          int numberOfSuccesses,
                          int sampleSize)Creates a new hypergeometric distribution. | 
| LaplaceDistribution(RandomGenerator rng,
                   double mu,
                   double beta)Build a new instance. | 
| LevyDistribution(RandomGenerator rng,
                double mu,
                double c)Creates a LevyDistribution. | 
| LogisticDistribution(RandomGenerator rng,
                    double mu,
                    double s)Build a new instance. | 
| LogNormalDistribution(RandomGenerator rng,
                     double scale,
                     double shape)Creates a log-normal distribution. | 
| LogNormalDistribution(RandomGenerator rng,
                     double scale,
                     double shape,
                     double inverseCumAccuracy)Creates a log-normal distribution. | 
| MixtureMultivariateNormalDistribution(RandomGenerator rng,
                                     List<Pair<Double,MultivariateNormalDistribution>> components)Creates a mixture model from a list of distributions and their
 associated weights. | 
| 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. | 
| NakagamiDistribution(RandomGenerator rng,
                    double mu,
                    double omega,
                    double inverseAbsoluteAccuracy)Build a new instance. | 
| NormalDistribution(RandomGenerator rng,
                  double mean,
                  double sd)Creates a normal distribution. | 
| NormalDistribution(RandomGenerator rng,
                  double mean,
                  double sd,
                  double inverseCumAccuracy)Creates a normal distribution. | 
| ParetoDistribution(RandomGenerator rng,
                  double scale,
                  double shape)Creates a Pareto distribution. | 
| ParetoDistribution(RandomGenerator rng,
                  double scale,
                  double shape,
                  double inverseCumAccuracy)Creates a Pareto 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)Creates a t distribution. | 
| 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)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.UniformRealDistribution(RandomGenerator, double, double)instead. | 
| WeibullDistribution(RandomGenerator rng,
                   double alpha,
                   double beta)Creates a Weibull 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. | 
| Modifier and Type | Method and Description | 
|---|---|
| static RandomGenerator | GeneticAlgorithm. getRandomGenerator()Returns the (static) random generator. | 
| Modifier and Type | Method and Description | 
|---|---|
| static void | GeneticAlgorithm. setRandomGenerator(RandomGenerator random)Set the (static) random generator. | 
| Modifier and Type | Method and Description | 
|---|---|
| RandomGenerator | KMeansPlusPlusClusterer. getRandomGenerator()Returns the random generator this instance will use. | 
| RandomGenerator | FuzzyKMeansClusterer. getRandomGenerator()Returns the random generator this instance will use. | 
| Constructor and Description | 
|---|
| FuzzyKMeansClusterer(int k,
                    double fuzziness,
                    int maxIterations,
                    DistanceMeasure measure,
                    double epsilon,
                    RandomGenerator random)Creates a new instance of a FuzzyKMeansClusterer. | 
| KMeansPlusPlusClusterer(int k,
                       int maxIterations,
                       DistanceMeasure measure,
                       RandomGenerator random)Build a clusterer. | 
| KMeansPlusPlusClusterer(int k,
                       int maxIterations,
                       DistanceMeasure measure,
                       RandomGenerator random,
                       KMeansPlusPlusClusterer.EmptyClusterStrategy emptyStrategy)Build a clusterer. | 
| Modifier and Type | Method and Description | 
|---|---|
| static FeatureInitializer | FeatureInitializerFactory. uniform(RandomGenerator rng,
       double min,
       double max)Uniform sampling of the given range. | 
| Constructor and Description | 
|---|
| CMAESOptimizer(int maxIterations,
              double stopFitness,
              boolean isActiveCMA,
              int diagonalOnly,
              int checkFeasableCount,
              RandomGenerator random,
              boolean generateStatistics,
              ConvergenceChecker<PointValuePair> checker) | 
| Constructor and Description | 
|---|
| MultiStartUnivariateOptimizer(UnivariateOptimizer optimizer,
                             int starts,
                             RandomGenerator generator)Create a multi-start optimizer from a single-start optimizer. | 
| Modifier and Type | Field and Description | 
|---|---|
| static RandomGenerator | CMAESOptimizer. DEFAULT_RANDOMGENERATORDeprecated.  Default value for  CMAESOptimizer.random. | 
| Constructor and Description | 
|---|
| CMAESOptimizer(int lambda,
              double[] inputSigma,
              int maxIterations,
              double stopFitness,
              boolean isActiveCMA,
              int diagonalOnly,
              int checkFeasableCount,
              RandomGenerator random,
              boolean generateStatistics)Deprecated. 
 | 
| CMAESOptimizer(int lambda,
              double[] inputSigma,
              int maxIterations,
              double stopFitness,
              boolean isActiveCMA,
              int diagonalOnly,
              int checkFeasableCount,
              RandomGenerator random,
              boolean generateStatistics,
              ConvergenceChecker<PointValuePair> checker)Deprecated. 
 | 
| CMAESOptimizer(int maxIterations,
              double stopFitness,
              boolean isActiveCMA,
              int diagonalOnly,
              int checkFeasableCount,
              RandomGenerator random,
              boolean generateStatistics,
              ConvergenceChecker<PointValuePair> checker)Deprecated.  | 
| Constructor and Description | 
|---|
| UnivariateMultiStartOptimizer(BaseUnivariateOptimizer<FUNC> optimizer,
                             int starts,
                             RandomGenerator generator)Deprecated.  Create a multi-start optimizer from a single-start optimizer. | 
| Modifier and Type | Class and Description | 
|---|---|
| class  | AbstractRandomGeneratorAbstract class implementing the  RandomGeneratorinterface. | 
| class  | AbstractWellThis abstract class implements the WELL class of pseudo-random number generator
 from François Panneton, Pierre L'Ecuyer and Makoto Matsumoto. | 
| class  | BitsStreamGeneratorBase 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  | JDKRandomGeneratorExtension of  java.util.Randomto implementRandomGenerator. | 
| class  | MersenneTwisterThis class implements a powerful pseudo-random number generator
 developed by Makoto Matsumoto and Takuji Nishimura during
 1996-1997. | 
| class  | RandomAdaptorExtension of  java.util.Randomwrapping aRandomGenerator. | 
| class  | SynchronizedRandomGeneratorAny  RandomGeneratorimplementation can be thread-safe if it
 is used through an instance of this class. | 
| class  | Well1024aThis class implements the WELL1024a pseudo-random number generator
 from François Panneton, Pierre L'Ecuyer and Makoto Matsumoto. | 
| class  | Well19937aThis class implements the WELL19937a pseudo-random number generator
 from François Panneton, Pierre L'Ecuyer and Makoto Matsumoto. | 
| class  | Well19937cThis class implements the WELL19937c pseudo-random number generator
 from François Panneton, Pierre L'Ecuyer and Makoto Matsumoto. | 
| class  | Well44497aThis class implements the WELL44497a pseudo-random number generator
 from François Panneton, Pierre L'Ecuyer and Makoto Matsumoto. | 
| class  | Well44497bThis class implements the WELL44497b pseudo-random number generator
 from François Panneton, Pierre L'Ecuyer and Makoto Matsumoto. | 
| class  | Well512aThis class implements the WELL512a pseudo-random number generator
 from François Panneton, Pierre L'Ecuyer and Makoto Matsumoto. | 
| Modifier and Type | Method and Description | 
|---|---|
| static RandomGenerator | RandomGeneratorFactory. createRandomGenerator(Random rng)Creates a  RandomDataGeneratorinstance that wraps aRandominstance. | 
| RandomGenerator | RandomDataGenerator. getRandomGenerator()Returns the RandomGenerator used to generate non-secure random data. | 
| Modifier and Type | Method and Description | 
|---|---|
| static Random | RandomAdaptor. createAdaptor(RandomGenerator randomGenerator)Factory method to create a  Randomusing the suppliedRandomGenerator. | 
| Constructor and Description | 
|---|
| EmpiricalDistribution(int binCount,
                     RandomGenerator generator)Creates a new EmpiricalDistribution with the specified bin count using the
 provided  RandomGeneratoras the source of random data. | 
| EmpiricalDistribution(RandomGenerator generator)Creates a new EmpiricalDistribution with default bin count using the
 provided  RandomGeneratoras 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  RandomGeneratoras
 the source of (non-secure) random data. | 
| RandomDataImpl(RandomGenerator rand)Deprecated.  Construct a RandomDataImpl using the supplied  RandomGeneratoras
 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  RandomGeneratorinstance. | 
| 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. | 
| Constructor and Description | 
|---|
| KolmogorovSmirnovTest(RandomGenerator rng)Deprecated.  | 
| Constructor and Description | 
|---|
| 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. | 
| Modifier and Type | Method and Description | 
|---|---|
| static void | MathArrays. shuffle(int[] list,
       int start,
       MathArrays.Position pos,
       RandomGenerator rng)Shuffle the entries of the given array, using the
 
 Fisher–Yates algorithm. | 
| static void | MathArrays. shuffle(int[] list,
       RandomGenerator rng)Shuffle the entries of the given array. | 
| Constructor and Description | 
|---|
| RandomPivotingStrategy(RandomGenerator random)Simple constructor. | 
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