Uses of Interface
dev.nm.stat.random.rng.multivariate.RandomVectorGenerator
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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 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)
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Uses of RandomVectorGenerator in dev.nm.stat.evt.evd.bivariate
Subinterfaces of RandomVectorGenerator in dev.nm.stat.evt.evd.bivariate Modifier and Type Interface 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 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 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 Description static List<double[]>
RNGUtils. nextN(RandomVectorGenerator rvg, int n)
Generatesn
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 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 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 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.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 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 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 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 Description class
MultivariateRandomProcess
This interface represents a multivariate random process a.k.a.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 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 Description VARIMASim(VARIMAModel arima, Vector[] lags, Vector[] innovations, RandomVectorGenerator rvg)
Construct a multivariate ARIMA model.VARIMASim(VARIMAModel arima, RandomVectorGenerator rvg)
Construct a multivariate ARIMA model.
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