Uses of Class
cern.jet.random.tdouble.engine.DoubleRandomEngine

Packages that use DoubleRandomEngine

cern.colt.matrix.tdouble.algo	Linear Algebraic matrix computations operating on DoubleMatrix2D and DoubleMatrix1D.
cern.jet.random.tdouble	Large variety of probability distributions featuring high performance generation of random numbers, CDF's and PDF's.
cern.jet.random.tdouble.engine	Engines generating strong uniformly distributed pseudo-random numbers; Needed by all JET probability distributions since they rely on uniform random numbers to generate random numbers from their own distribution.
cern.jet.random.tdouble.sampling	Samples (picks) random subsets of data sequences.
cern.jet.stat.tdouble.quantile	Scalable algorithms and data structures to compute approximate quantiles over very large data sequences.
hep.aida.tdouble.bin	Multisets (bags) with efficient statistics operations defined upon; This package requires the Colt distribution.

Uses of DoubleRandomEngine in cern.colt.matrix.tdouble.algo

Methods in cern.colt.matrix.tdouble.algo with parameters of type DoubleRandomEngine

static DoubleMatrix1D	DoubleStatistic.viewSample(DoubleMatrix1D matrix, double fraction, DoubleRandomEngine randomGenerator) Constructs and returns a sampling view with a size of round(matrix.size() * fraction).
static DoubleMatrix2D	DoubleStatistic.viewSample(DoubleMatrix2D matrix, double rowFraction, double columnFraction, DoubleRandomEngine randomGenerator) Constructs and returns a sampling view with round(matrix.rows() * rowFraction) rows and round(matrix.columns() * columnFraction) columns.
static DoubleMatrix3D	DoubleStatistic.viewSample(DoubleMatrix3D matrix, double sliceFraction, double rowFraction, double columnFraction, DoubleRandomEngine randomGenerator) Constructs and returns a sampling view with round(matrix.slices() * sliceFraction) slices and round(matrix.rows() * rowFraction) rows and round(matrix.columns() * columnFraction) columns.

Uses of DoubleRandomEngine in cern.jet.random.tdouble

Methods in cern.jet.random.tdouble that return DoubleRandomEngine

static DoubleRandomEngine

AbstractDoubleDistribution.makeDefaultGenerator() Constructs and returns a new uniform random number generation engine seeded with the current time.

Methods in cern.jet.random.tdouble with parameters of type DoubleRandomEngine

static double	Distributions.nextBurr1(double r, int nr, DoubleRandomEngine randomGenerator) Returns a random number from the Burr II, VII, VIII, X Distributions.
static double	Distributions.nextBurr2(double r, double k, int nr, DoubleRandomEngine randomGenerator) Returns a random number from the Burr III, IV, V, VI, IX, XII distributions.
static double	Distributions.nextCauchy(DoubleRandomEngine randomGenerator) Returns a cauchy distributed random number from the standard Cauchy distribution C(0,1).
static double	Distributions.nextErlang(double variance, double mean, DoubleRandomEngine randomGenerator) Returns an erlang distributed random number with the given variance and mean.
static int	Distributions.nextGeometric(double p, DoubleRandomEngine randomGenerator) Returns a discrete geometric distributed random number; Definition.
static double	Distributions.nextLambda(double l3, double l4, DoubleRandomEngine randomGenerator) Returns a lambda distributed random number with parameters l3 and l4.
static double	Distributions.nextLaplace(DoubleRandomEngine randomGenerator) Returns a Laplace (Double Exponential) distributed random number from the standard Laplace distribution L(0,1).
static double	Distributions.nextLogistic(DoubleRandomEngine randomGenerator) Returns a random number from the standard Logistic distribution Log(0,1).
static double	Distributions.nextPowLaw(double alpha, double cut, DoubleRandomEngine randomGenerator) Returns a power-law distributed random number with the given exponent and lower cutoff.
static double	Distributions.nextTriangular(DoubleRandomEngine randomGenerator) Returns a random number from the standard Triangular distribution in (-1,1).
static double	Distributions.nextWeibull(double alpha, double beta, DoubleRandomEngine randomGenerator) Returns a weibull distributed random number.
static int	Distributions.nextZipfInt(double z, DoubleRandomEngine randomGenerator) Returns a zipfian distributed random number with the given skew.
static void	DoubleUniform.staticSetRandomEngine(DoubleRandomEngine randomGenerator) Sets the uniform random number generation engine shared by all static methods.

Constructors in cern.jet.random.tdouble with parameters of type DoubleRandomEngine

Beta(double alpha, double beta, DoubleRandomEngine randomGenerator)
Constructs a Beta distribution.

Binomial(int n, double p, DoubleRandomEngine randomGenerator)
Constructs a binomial distribution.

BreitWigner(double mean, double gamma, double cut, DoubleRandomEngine randomGenerator)
Constructs a BreitWigner distribution.

BreitWignerMeanSquare(double mean, double gamma, double cut, DoubleRandomEngine randomGenerator)
Constructs a mean-squared BreitWigner distribution.

ChiSquare(double freedom, DoubleRandomEngine randomGenerator)
Constructs a ChiSquare distribution.

DoubleUniform(double min, double max, DoubleRandomEngine randomGenerator)
Constructs a uniform distribution with the given minimum and maximum.

DoubleUniform(DoubleRandomEngine randomGenerator)
Constructs a uniform distribution with min=0.0 and max=1.0.

Empirical(double[] pdf, int interpolationType, DoubleRandomEngine randomGenerator)
Constructs an Empirical distribution.

EmpiricalWalker(double[] pdf, int interpolationType, DoubleRandomEngine randomGenerator)
Constructs an Empirical distribution.

Exponential(double lambda, DoubleRandomEngine randomGenerator)
Constructs a Negative Exponential distribution.

ExponentialPower(double tau, DoubleRandomEngine randomGenerator)
Constructs an Exponential Power distribution.

Gamma(double alpha, double lambda, DoubleRandomEngine randomGenerator)
Constructs a Gamma distribution.

Hyperbolic(double alpha, double beta, DoubleRandomEngine randomGenerator)
Constructs a Beta distribution.

HyperGeometric(int N, int s, int n, DoubleRandomEngine randomGenerator)
Constructs a HyperGeometric distribution.

Logarithmic(double p, DoubleRandomEngine randomGenerator)
Constructs a Logarithmic distribution.

NegativeBinomial(int n, double p, DoubleRandomEngine randomGenerator)
Constructs a Negative Binomial distribution.

Normal(double mean, double standardDeviation, DoubleRandomEngine randomGenerator)
Constructs a normal (gauss) distribution.

Poisson(double mean, DoubleRandomEngine randomGenerator)
Constructs a poisson distribution.

PoissonSlow(double mean, DoubleRandomEngine randomGenerator)
Constructs a poisson distribution.

StudentT(double freedom, DoubleRandomEngine randomGenerator)
Constructs a StudentT distribution.

VonMises(double freedom, DoubleRandomEngine randomGenerator)
Constructs a Von Mises distribution.

Zeta(double ro, double pk, DoubleRandomEngine randomGenerator)
Constructs a Zeta distribution.

Uses of DoubleRandomEngine in cern.jet.random.tdouble.engine

Subclasses of DoubleRandomEngine in cern.jet.random.tdouble.engine

class	DoubleMersenneTwister MersenneTwister (MT19937) is one of the strongest uniform pseudo-random number generators known so far; at the same time it is quick.
class	DRand Quick medium quality uniform pseudo-random number generator.
class	MersenneTwister64 Same as MersenneTwister except that method raw() returns 64 bit random numbers instead of 32 bit random numbers.

Methods in cern.jet.random.tdouble.engine that return DoubleRandomEngine

static DoubleRandomEngine

DoubleRandomEngine.makeDefault() Constructs and returns a new uniform random number engine seeded with the current time.

Uses of DoubleRandomEngine in cern.jet.random.tdouble.sampling

Methods in cern.jet.random.tdouble.sampling that return DoubleRandomEngine

DoubleRandomEngine

DoubleRandomSamplingAssistant.getRandomGenerator() Returns the used random generator.

Methods in cern.jet.random.tdouble.sampling with parameters of type DoubleRandomEngine

static void

DoubleRandomSampler.sample(long n, long N, int count, long low, long[] values, int fromIndex, DoubleRandomEngine randomGenerator) Efficiently computes a sorted random set of count elements from the interval [low,low+N-1].

Constructors in cern.jet.random.tdouble.sampling with parameters of type DoubleRandomEngine

DoubleRandomSampler(long n, long N, long low, DoubleRandomEngine randomGenerator)
Constructs a random sampler that computes and delivers sorted random sets in blocks.

DoubleRandomSamplingAssistant(long n, long N, DoubleRandomEngine randomGenerator)
Constructs a random sampler that samples n random elements from an input sequence of N elements.

WeightedDoubleRandomSampler(int weight, DoubleRandomEngine randomGenerator)
Chooses exactly one random element from successive blocks of weight input elements each.

Uses of DoubleRandomEngine in cern.jet.stat.tdouble.quantile

Methods in cern.jet.stat.tdouble.quantile with parameters of type DoubleRandomEngine

static DoubleQuantileFinder

DoubleQuantileFinderFactory.newDoubleQuantileFinder(boolean known_N, long N, double epsilon, double delta, int quantiles, DoubleRandomEngine generator) Returns a quantile finder that minimizes the amount of memory needed under the user provided constraints.

Uses of DoubleRandomEngine in hep.aida.tdouble.bin

Methods in hep.aida.tdouble.bin with parameters of type DoubleRandomEngine

void	DynamicDoubleBin1D.sample(int n, boolean withReplacement, DoubleRandomEngine randomGenerator, DoubleBuffer buffer) Uniformly samples (chooses) n random elements with or without replacement from the contained elements and adds them to the given buffer.
DynamicDoubleBin1D	DynamicDoubleBin1D.sampleBootstrap(DynamicDoubleBin1D other, int resamples, DoubleRandomEngine randomGenerator, DoubleBinBinFunction1D function) Generic bootstrap resampling.

Constructors in hep.aida.tdouble.bin with parameters of type DoubleRandomEngine

QuantileDoubleBin1D(boolean known_N, long N, double epsilon, double delta, int quantiles, DoubleRandomEngine randomGenerator)
Equivalent to new QuantileBin1D(known_N, N, epsilon, delta, quantiles, randomGenerator, false, false, 2) .

QuantileDoubleBin1D(boolean known_N, long N, double epsilon, double delta, int quantiles, DoubleRandomEngine randomGenerator, boolean hasSumOfLogarithms, boolean hasSumOfInversions, int maxOrderForSumOfPowers)
Constructs and returns an empty bin that, under the given constraints, minimizes the amount of memory needed.