| 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.random
RNG instance used to generate samples from the distribution.
|
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.
|
| 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_RANDOMGENERATOR
Deprecated.
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 |
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.
|
| Modifier and Type | Method and Description |
|---|---|
static RandomGenerator |
RandomGeneratorFactory.createRandomGenerator(Random rng)
Creates a
RandomDataGenerator instance that wraps a
Random instance. |
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
Random using the supplied
RandomGenerator. |
| Constructor and Description |
|---|
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.
|
| 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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