Uses of Interface
dev.nm.stat.random.rng.multivariate.RandomVectorGenerator

Packages that use RandomVectorGenerator

Package	Description
dev.nm.solver.multivariate.unconstrained.annealing.annealingfunction
dev.nm.stat.evt.evd.bivariate
dev.nm.stat.random.rng
dev.nm.stat.random.rng.concurrent.cache
dev.nm.stat.random.rng.multivariate
dev.nm.stat.random.rng.multivariate.mcmc.hybrid
dev.nm.stat.random.rng.multivariate.mcmc.metropolis
dev.nm.stat.stochasticprocess.multivariate.random
dev.nm.stat.timeseries.linear.multivariate.arima

Uses of RandomVectorGenerator in dev.nm.solver.multivariate.unconstrained.annealing.annealingfunction

Constructors in dev.nm.solver.multivariate.unconstrained.annealing.annealingfunction with parameters of type RandomVectorGenerator

Constructor and Description
BoltzAnnealingFunction(RandomVectorGenerator rvg) Constructs a new instance that uses a given RVG.
FastAnnealingFunction(RandomVectorGenerator rvg) Constructs a new instance that uses a given RVG.
SimpleAnnealingFunction(RandomVectorGenerator rvg)

Uses of RandomVectorGenerator in dev.nm.stat.evt.evd.bivariate

Subinterfaces of RandomVectorGenerator in dev.nm.stat.evt.evd.bivariate

Modifier and Type	Interface and Description
interface	BivariateEVD Bivariate Extreme Value (BEV) distribution is the joint distribution of component-wise maxima of two-dimensional iid random vectors.

Classes in dev.nm.stat.evt.evd.bivariate that implement RandomVectorGenerator

Modifier and Type	Class and Description
class	AbstractBivariateEVD
class	BivariateEVDAsymmetricLogistic The bivariate asymmetric logistic model.
class	BivariateEVDAsymmetricMixed The asymmetric mixed model.
class	BivariateEVDAsymmetricNegativeLogistic The bivariate asymmetric negative logistic model.
class	BivariateEVDBilogistic The bilogistic model.
class	BivariateEVDColesTawn The Coles-Tawn model.
class	BivariateEVDHuslerReiss The Husler-Reiss model.
class	BivariateEVDLogistic The bivariate logistic model.
class	BivariateEVDNegativeBilogistic The negative bilogistic model.
class	BivariateEVDNegativeLogistic The bivariate negative logistic model.

Uses of RandomVectorGenerator in dev.nm.stat.random.rng

Methods in dev.nm.stat.random.rng that return RandomVectorGenerator

Modifier and Type	Method and Description
static RandomVectorGenerator	RNGUtils.synchronizedRVG(RandomVectorGenerator rng) Returns a synchronized (thread-safe) RandomVectorGenerator backed by a specified generator.

Methods in dev.nm.stat.random.rng with parameters of type RandomVectorGenerator

Modifier and Type	Method and Description
static List<double[]>	RNGUtils.nextN(RandomVectorGenerator rvg, int n) Generates n random vectors from a given random vector generator.
static RandomVectorGenerator	RNGUtils.synchronizedRVG(RandomVectorGenerator rng) Returns a synchronized (thread-safe) RandomVectorGenerator backed by a specified generator.

Uses of RandomVectorGenerator in dev.nm.stat.random.rng.concurrent.cache

Classes in dev.nm.stat.random.rng.concurrent.cache that implement RandomVectorGenerator

Modifier and Type	Class and Description
class	ConcurrentCachedRVG This is a fast thread-safe wrapper for random vector generators.

Constructors in dev.nm.stat.random.rng.concurrent.cache with parameters of type RandomVectorGenerator

Constructor and Description
ConcurrentCachedRVG(RandomVectorGenerator rvg) Constructs a new instance which wraps the given random vector generator and uses a cache which has 8 entries per available core.
ConcurrentCachedRVG(RandomVectorGenerator rvg, int cacheSize) Constructs a new instance which wraps the given random vector generator and uses a cache of the specified size.

Uses of RandomVectorGenerator in dev.nm.stat.random.rng.multivariate

Classes in dev.nm.stat.random.rng.multivariate that implement RandomVectorGenerator

Modifier and Type	Class and Description
class	BurnInRVG A burn-in random number generator discards the first M samples.
class	HypersphereRVG Generates uniformly distributed points on the surface of a hypersphere.
class	IID An i.i.d. random vector has elements drawn from the same distribution.
class	MultinomialRVG A multinomial distribution puts N objects into K bins according to the bins' probabilities.
class	NormalRVG A multivariate Normal random vector is said to be p-variate normally distributed if every linear combination of its p components has a univariate normal distribution.
class	ThinRVG Thinning is a scheme that returns every m-th item, discarding the last m-1 items for each draw.
class	UniformDistributionOverBox This random vector generator uniformly samples points over a box region.

Constructors in dev.nm.stat.random.rng.multivariate with parameters of type RandomVectorGenerator

Constructor and Description
BurnInRVG(RandomVectorGenerator rvg, int burnInSamples) Construct a burn-in RVG.
ThinRVG(RandomVectorGenerator rvg, int m) Constructs a thinned RVG.

Uses of RandomVectorGenerator in dev.nm.stat.random.rng.multivariate.mcmc.hybrid

Classes in dev.nm.stat.random.rng.multivariate.mcmc.hybrid that implement RandomVectorGenerator

Modifier and Type	Class and Description
class	AbstractHybridMCMC Hybrid Monte Carlo, or Hamiltonian Monte Carlo, is a method that combines the traditional Metropolis algorithm, with molecular dynamics simulation.
class	ErgodicHybridMCMC A simple decorator which will randomly vary dt between each sample.
class	HybridMCMC This class implements a hybrid MCMC algorithm.
class	MultipointHybridMCMC A multi-point Hybrid Monte Carlo is an extension of HybridMCMC, where during the proposal generation instead of considering only the last configuration after the dynamics simulation, we pick a proposal from a window of the last M configurations.

Uses of RandomVectorGenerator in dev.nm.stat.random.rng.multivariate.mcmc.metropolis

Classes in dev.nm.stat.random.rng.multivariate.mcmc.metropolis that implement RandomVectorGenerator

Modifier and Type	Class and Description
class	AbstractMetropolis The Metropolis algorithm is a Markov Chain Monte Carlo algorithm, which requires only a function f proportional to the PDF from which we wish to sample.
class	Metropolis This basic Metropolis implementation assumes using symmetric proposal function.
class	MetropolisHastings A generalization of the Metropolis algorithm, which allows asymmetric proposal functions.
class	RobustAdaptiveMetropolis A variation of Metropolis, that uses the estimated covariance of the target distribution in the proposal distribution, based on a paper by Vihola (2011).

Uses of RandomVectorGenerator in dev.nm.stat.stochasticprocess.multivariate.random

Classes in dev.nm.stat.stochasticprocess.multivariate.random that implement RandomVectorGenerator

Modifier and Type	Class and Description
class	MultivariateRandomProcess This interface represents a multivariate random process a.k.a. stochastic process.
class	MultivariateRandomWalk This is the Random Walk construction of a multivariate stochastic process per SDE specification.

Uses of RandomVectorGenerator in dev.nm.stat.timeseries.linear.multivariate.arima

Classes in dev.nm.stat.timeseries.linear.multivariate.arima that implement RandomVectorGenerator

Modifier and Type	Class and Description
class	VARIMASim This class simulates a multivariate ARIMA process.

Constructors in dev.nm.stat.timeseries.linear.multivariate.arima with parameters of type RandomVectorGenerator

Constructor and Description
VARIMASim(VARIMAModel arima, RandomVectorGenerator rvg) Construct a multivariate ARIMA model.
VARIMASim(VARIMAModel arima, Vector[] lags, Vector[] innovations, RandomVectorGenerator rvg) Construct a multivariate ARIMA model.