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Colt 1.0.2 | |||||||||
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Packages that use RandomElement | |
cern.colt.matrix.doublealgo | Double matrix algorithms such as print formatting, sorting, partitioning and statistics. |
cern.jet.random | Large variety of probability distributions featuring high performance generation of random numbers, CDF's and PDF's. |
cern.jet.random.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.sampling | Samples (picks) random subsets of data sequences. |
cern.jet.stat.quantile | Scalable algorithms and data structures to compute approximate quantiles over very large data sequences. |
edu.cornell.lassp.houle.RngPack | More strong uniform pseudo-random number generators. |
hep.aida.bin | Multisets (bags) with efficient statistics operations defined upon; This package requires the Colt distribution. |
Uses of RandomElement in cern.colt.matrix.doublealgo |
Methods in cern.colt.matrix.doublealgo with parameters of type RandomElement | |
static DoubleMatrix1D |
Statistic.viewSample(DoubleMatrix1D matrix,
double fraction,
RandomElement randomGenerator)
Constructs and returns a sampling view with a size of round(matrix.size() * fraction). |
static DoubleMatrix2D |
Statistic.viewSample(DoubleMatrix2D matrix,
double rowFraction,
double columnFraction,
RandomElement randomGenerator)
Constructs and returns a sampling view with round(matrix.rows() * rowFraction) rows and round(matrix.columns() * columnFraction) columns. |
static DoubleMatrix3D |
Statistic.viewSample(DoubleMatrix3D matrix,
double sliceFraction,
double rowFraction,
double columnFraction,
RandomElement 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 RandomElement in cern.jet.random |
Methods in cern.jet.random that return RandomElement | |
static RandomElement |
AbstractDistribution.makeDefaultGenerator()
Constructs and returns a new uniform random number generation engine seeded with the current time. |
Methods in cern.jet.random with parameters of type RandomElement | |
static double |
Distributions.nextBurr1(double r,
int nr,
RandomElement randomGenerator)
Returns a random number from the Burr II, VII, VIII, X Distributions. |
static double |
Distributions.nextBurr2(double r,
double k,
int nr,
RandomElement randomGenerator)
Returns a random number from the Burr III, IV, V, VI, IX, XII distributions. |
static double |
Distributions.nextCauchy(RandomElement randomGenerator)
Returns a cauchy distributed random number from the standard Cauchy distribution C(0,1). |
static double |
Distributions.nextErlang(double variance,
double mean,
RandomElement randomGenerator)
Returns an erlang distributed random number with the given variance and mean. |
static int |
Distributions.nextGeometric(double p,
RandomElement randomGenerator)
Returns a discrete geometric distributed random number; Definition. |
static double |
Distributions.nextLambda(double l3,
double l4,
RandomElement randomGenerator)
Returns a lambda distributed random number with parameters l3 and l4. |
static double |
Distributions.nextLaplace(RandomElement randomGenerator)
Returns a Laplace (Double Exponential) distributed random number from the standard Laplace distribution L(0,1). |
static double |
Distributions.nextLogistic(RandomElement randomGenerator)
Returns a random number from the standard Logistic distribution Log(0,1). |
static double |
Distributions.nextPowLaw(double alpha,
double cut,
RandomElement randomGenerator)
Returns a power-law distributed random number with the given exponent and lower cutoff. |
static double |
Distributions.nextTriangular(RandomElement randomGenerator)
Returns a random number from the standard Triangular distribution in (-1,1). |
static double |
Distributions.nextWeibull(double alpha,
double beta,
RandomElement randomGenerator)
Returns a weibull distributed random number. |
static int |
Distributions.nextZipfInt(double z,
RandomElement randomGenerator)
Returns a zipfian distributed random number with the given skew. |
static void |
Uniform.staticSetRandomEngine(RandomElement randomGenerator)
Sets the uniform random number generation engine shared by all static methods. |
Constructors in cern.jet.random with parameters of type RandomElement | |
NegativeBinomial(int n,
double p,
RandomElement randomGenerator)
Constructs a Negative Binomial distribution. |
|
EmpiricalWalker(double[] pdf,
int interpolationType,
RandomElement randomGenerator)
Constructs an Empirical distribution. |
|
Zeta(double ro,
double pk,
RandomElement randomGenerator)
Constructs a Zeta distribution. |
|
BreitWigner(double mean,
double gamma,
double cut,
RandomElement randomGenerator)
Constructs a BreitWigner distribution. |
|
Empirical(double[] pdf,
int interpolationType,
RandomElement randomGenerator)
Constructs an Empirical distribution. |
|
StudentT(double freedom,
RandomElement randomGenerator)
Constructs a StudentT distribution. |
|
Binomial(int n,
double p,
RandomElement randomGenerator)
Constructs a binomial distribution. |
|
Exponential(double lambda,
RandomElement randomGenerator)
Constructs a Negative Exponential distribution. |
|
Logarithmic(double p,
RandomElement randomGenerator)
Constructs a Logarithmic distribution. |
|
Hyperbolic(double alpha,
double beta,
RandomElement randomGenerator)
Constructs a Beta distribution. |
|
ChiSquare(double freedom,
RandomElement randomGenerator)
Constructs a ChiSquare distribution. |
|
HyperGeometric(int N,
int s,
int n,
RandomElement randomGenerator)
Constructs a HyperGeometric distribution. |
|
Gamma(double alpha,
double lambda,
RandomElement randomGenerator)
Constructs a Gamma distribution. |
|
VonMises(double freedom,
RandomElement randomGenerator)
Constructs a Von Mises distribution. |
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Normal(double mean,
double standardDeviation,
RandomElement randomGenerator)
Constructs a normal (gauss) distribution. |
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Beta(double alpha,
double beta,
RandomElement randomGenerator)
Constructs a Beta distribution. |
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ExponentialPower(double tau,
RandomElement randomGenerator)
Constructs an Exponential Power distribution. |
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PoissonSlow(double mean,
RandomElement randomGenerator)
Constructs a poisson distribution. |
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Poisson(double mean,
RandomElement randomGenerator)
Constructs a poisson distribution. |
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BreitWignerMeanSquare(double mean,
double gamma,
double cut,
RandomElement randomGenerator)
Constructs a mean-squared BreitWigner distribution. |
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Uniform(double min,
double max,
RandomElement randomGenerator)
Constructs a uniform distribution with the given minimum and maximum. |
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Uniform(RandomElement randomGenerator)
Constructs a uniform distribution with min=0.0 and max=1.0. |
Uses of RandomElement in cern.jet.random.engine |
Subclasses of RandomElement in cern.jet.random.engine | |
class |
DRand
Quick medium quality uniform pseudo-random number generator. |
class |
MersenneTwister
MersenneTwister (MT19937) is one of the strongest uniform pseudo-random number generators known so far; at the same time it is quick. |
class |
MersenneTwister64
Same as MersenneTwister except that method raw() returns 64 bit random numbers instead of 32 bit random numbers. |
class |
RandomEngine
Abstract base class for uniform pseudo-random number generating engines. |
Methods in cern.jet.random.engine that return RandomElement | |
static RandomElement |
RandomEngine.makeDefault()
Constructs and returns a new uniform random number engine seeded with the current time. |
Uses of RandomElement in cern.jet.random.sampling |
Methods in cern.jet.random.sampling that return RandomElement | |
RandomElement |
RandomSamplingAssistant.getRandomGenerator()
Returns the used random generator. |
Methods in cern.jet.random.sampling with parameters of type RandomElement | |
static void |
RandomSampler.sample(long n,
long N,
int count,
long low,
long[] values,
int fromIndex,
RandomElement randomGenerator)
Efficiently computes a sorted random set of count elements from the interval [low,low+N-1]. |
Constructors in cern.jet.random.sampling with parameters of type RandomElement | |
WeightedRandomSampler(int weight,
RandomElement randomGenerator)
Chooses exactly one random element from successive blocks of weight input elements each. |
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RandomSamplingAssistant(long n,
long N,
RandomElement randomGenerator)
Constructs a random sampler that samples n random elements from an input sequence of N elements. |
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RandomSampler(long n,
long N,
long low,
RandomElement randomGenerator)
Constructs a random sampler that computes and delivers sorted random sets in blocks. |
Uses of RandomElement in cern.jet.stat.quantile |
Methods in cern.jet.stat.quantile with parameters of type RandomElement | |
static DoubleQuantileFinder |
QuantileFinderFactory.newDoubleQuantileFinder(boolean known_N,
long N,
double epsilon,
double delta,
int quantiles,
RandomElement generator)
Returns a quantile finder that minimizes the amount of memory needed under the user provided constraints. |
Uses of RandomElement in edu.cornell.lassp.houle.RngPack |
Subclasses of RandomElement in edu.cornell.lassp.houle.RngPack | |
class |
RandomJava
RandomJava is a class wrapper for the Math.random()
generator that comes with Java. |
class |
RandomSeedable
RandomSeedable is an abstract class that extends the
RandomElement class to include the ability to
automatically generate a valid long seed from the clock. |
class |
RandomShuffle
RandomShuffle uses one random number generator to shuffle the numbers produced by another to obliterate sequential correlations. |
class |
Ranecu
Ranecu is an advanced multiplicative linear congruential random number generator with a period of aproximately 1018. |
class |
Ranlux
RANLUX is an advanced pseudo-random number generator based on the RCARRY algorithm proposed in 1991 by Marsaglia and Zaman. |
class |
Ranmar
RANMAR is a lagged Fibonacci generator proposed by Marsaglia and Zaman and is a good research grade generator. |
Constructors in edu.cornell.lassp.houle.RngPack with parameters of type RandomElement | |
RandomShuffle(RandomElement ga,
RandomElement gb,
int ds)
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Uses of RandomElement in hep.aida.bin |
Methods in hep.aida.bin with parameters of type RandomElement | |
void |
DynamicBin1D.sample(int n,
boolean withReplacement,
RandomElement randomGenerator,
DoubleBuffer buffer)
Uniformly samples (chooses) n random elements with or without replacement from the contained elements and adds them to the given buffer. |
DynamicBin1D |
DynamicBin1D.sampleBootstrap(DynamicBin1D other,
int resamples,
RandomElement randomGenerator,
BinBinFunction1D function)
Generic bootstrap resampling. |
Constructors in hep.aida.bin with parameters of type RandomElement | |
QuantileBin1D(boolean known_N,
long N,
double epsilon,
double delta,
int quantiles,
RandomElement randomGenerator)
Equivalent to new QuantileBin1D(known_N, N, epsilon, delta, quantiles, randomGenerator, false, false, 2). |
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QuantileBin1D(boolean known_N,
long N,
double epsilon,
double delta,
int quantiles,
RandomElement randomGenerator,
boolean hasSumOfLogarithms,
boolean hasSumOfInversions,
int maxOrderForSumOfPowers)
Constructs and returns an empty bin that, under the given constraints, minimizes the amount of memory needed. |
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Colt 1.0.2 | |||||||||
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