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#Com.numericalmethod.suanshu.stats.random.rng.univariate Classes and Interfaces - 48 results found.
| Name | Description | Type | Package | Framework |
| BernoulliTrial | A Bernoulli trial (or binomial trial) is a random experiment with exactly two possible outcomes, "success" and "failure", in which the probability of success, p, is the same every time | Class | com.numericalmethod.suanshu.stats.random.rng.univariate | SuanShu |
| BinomialRNG | This random number generator samples from the binomial distribution. | Class | com.numericalmethod.suanshu.stats.random.rng.univariate | SuanShu |
| BoxMuller | The Box-Muller transform (by George Edward Pelham Box and Mervin Edgar Muller 1958) is a pseudo-random number sampling method for generating pairs of independent standard | Class | com.numericalmethod.suanshu.stats.random.rng.univariate.normal | SuanShu |
| BurnInRNG | A burn-in random number generator discards the first M samples. | Class | com.numericalmethod.suanshu.stats.random.rng.univariate | SuanShu |
| Cheng1978 | Cheng, 1978, is a new rejection method for generating beta variates. | Class | com.numericalmethod.suanshu.stats.random.rng.univariate.beta | SuanShu |
| CompositeLinearCongruentialGenerator | A composite generator combines a number of simple LinearCongruentialGenerator, such as Lehmer, to form one longer period generator by first summing values and then taking modulus. | Class | com.numericalmethod.suanshu.stats.random.rng.univariate.uniform.linear | SuanShu |
| ConcurrentStandardNormalRNG | Class | com.numericalmethod.suanshu.stats.random.rng.univariate.normal | SuanShu | |
| DynamicCreator | Performs the Dynamic Creation algorithm (DC) to generate parameters for MersenneTwister. | Class | com.numericalmethod.suanshu.stats.random.rng.univariate.uniform.mersennetwister.dynamiccreation | SuanShu |
| DynamicCreatorException | Indicates that a problem has occurred in the dynamic creation process, usually because suitable parameters were not found. | Class | com.numericalmethod.suanshu.stats.random.rng.univariate.uniform.mersennetwister.dynamiccreation | SuanShu |
| InverseTransformSampling | Inverse transform sampling (also known as inversion sampling, the inverse probability integral transform, the inverse transformation method, Smirnov transform, golden rule, etc. | Class | com.numericalmethod.suanshu.stats.random.rng.univariate | SuanShu |
| InverseTransformSamplingExpRNG | This is a pseudo random number generator that samples from the exponential distribution using the inverse transform sampling method. | Class | com.numericalmethod.suanshu.stats.random.rng.univariate.exp | SuanShu |
| InverseTransformSamplingGammaRNG | This is a pseudo random number generator that samples from the gamma distribution using the inverse transform sampling method. | Class | com.numericalmethod.suanshu.stats.random.rng.univariate.gamma | SuanShu |
| InverseTransformSamplingTruncatedNormalRNG | A random variate x defined as x = Phi^{-1}( Phi(alpha) + Ucdot(Phi(eta)-Phi(alpha)))sigma + mu | Class | com.numericalmethod.suanshu.stats.random.rng.univariate.normal.truncated | SuanShu |
| Knuth1969 | This is a random number generator that generates random deviates according to the Poisson Generating Poisson-distributed random variables | Class | com.numericalmethod.suanshu.stats.random.rng.univariate.poisson | SuanShu |
| KunduGupta2007 | Kundu-Gupta propose a very convenient way to generate gamma random variables using generalized exponential distribution, | Class | com.numericalmethod.suanshu.stats.random.rng.univariate.gamma | SuanShu |
| LEcuyer | This is the uniform random number generator recommended by L'Ecuyer in 1996. | Class | com.numericalmethod.suanshu.stats.random.rng.univariate.uniform.linear | SuanShu |
| Lehmer | Lehmer proposed a general linear congruential generator that generates pseudo-random numbers in xi+1 = (a * xi + c) mod m | Class | com.numericalmethod.suanshu.stats.random.rng.univariate.uniform.linear | SuanShu |
| LinearCongruentialGenerator | A linear congruential generator (LCG) produces a sequence of pseudo-random numbers based on a linear recurrence relation. | Interface | com.numericalmethod.suanshu.stats.random.rng.univariate.uniform.linear | SuanShu |
| LogNormalRNG | This random number generator samples from the log-normal distribution. | Class | com.numericalmethod.suanshu.stats.random.rng.univariate | SuanShu |
| MarsagliaBray1964 | The polar method (attributed to George Marsaglia, 1964) is a pseudo-random number sampling method for generating a pair of independent standard normal random variables. | Class | com.numericalmethod.suanshu.stats.random.rng.univariate.normal | SuanShu |
| MarsagliaTsang2000 | Marsaglia-Tsang is a procedure for generating a gamma variate as the cube of a suitably scaled normal variate. | Class | com.numericalmethod.suanshu.stats.random.rng.univariate.gamma | SuanShu |
| MersenneExponent | enum MersenneExponentThe value of a Mersenne Exponent p is a parameter for creating a Mersenne-Twister random | Class | com.numericalmethod.suanshu.stats.random.rng.univariate.uniform.mersennetwister.dynamiccreation | SuanShu |
| MersenneTwister | Mersenne Twister is one of the best pseudo random number generators available. | Class | com.numericalmethod.suanshu.stats.random.rng.univariate.uniform.mersennetwister | SuanShu |
| MersenneTwisterParam | Immutable parameters for creating a MersenneTwister RNG. | Class | com.numericalmethod.suanshu.stats.random.rng.univariate.uniform.mersennetwister | SuanShu |
| MersenneTwisterParamSearcher | Searches for Mersenne-Twister parameters. | Class | com.numericalmethod.suanshu.stats.random.rng.univariate.uniform.mersennetwister.dynamiccreation | SuanShu |
| MRG | A Multiple Recursive Generator (MRG) is a linear congruential generator which takes this form: xi = (a1 * xi-1 + a2 * xi-2 + . | Class | com.numericalmethod.suanshu.stats.random.rng.univariate.uniform.linear | SuanShu |
| MWC8222 | Marsaglia's MWC256 (also known as MWC8222) is a multiply-with-carry generator. | Class | com.numericalmethod.suanshu.stats.random.rng.univariate.uniform | SuanShu |
| NormalRNG | This is a random number generator that generates random deviates according to the NormalSee Also:Wikipedia: Normal | Class | com.numericalmethod.suanshu.stats.random.rng.univariate.normal | SuanShu |
| RandomBetaGenerator | This is a random number generator that generates random deviates according to the Beta distribution. | Interface | com.numericalmethod.suanshu.stats.random.rng.univariate.beta | SuanShu |
| RandomExpGenerator | This is a random number generator that generates random deviates according to the exponential distribution. | Interface | com.numericalmethod.suanshu.stats.random.rng.univariate.exp | SuanShu |
| RandomGammaGenerator | This is a random number generator that generates random deviates according to the Gamma distribution. | Interface | com.numericalmethod.suanshu.stats.random.rng.univariate.gamma | SuanShu |
| RandomLongGenerator | A (pseudo) random number generator that generates a sequence of longs that lack any pattern and are uniformly distributed. | Interface | com.numericalmethod.suanshu.stats.random.rng.univariate | SuanShu |
| RandomNumberGenerator | A (pseudo) random number generator is an algorithm designed to generate a sequence of numbers that lack any pattern. | Interface | com.numericalmethod.suanshu.stats.random.rng.univariate | SuanShu |
| RandomStandardNormalGenerator | Interface | com.numericalmethod.suanshu.stats.random.rng.univariate.normal | SuanShu | |
| RayleighRNG | This random number generator samples from the Rayleigh distribution using the inverse transform sampling method. | Class | com.numericalmethod.suanshu.stats.random.rng.univariate | SuanShu |
| SHR0 | SHR0 is a simple uniform random number generator. | Class | com.numericalmethod.suanshu.stats.random.rng.univariate.uniform | SuanShu |
| SHR3 | SHR3 is a 3-shift-register generator with period 2^32-1. | Class | com.numericalmethod.suanshu.stats.random.rng.univariate.uniform | SuanShu |
| StandardNormalRNG | An alias for Zignor2005 to provide a default implementation for sampling from the standard Normal distribution. | Class | com.numericalmethod.suanshu.stats.random.rng.univariate.normal | SuanShu |
| ThinRNG | Thinning is a scheme that returns every m-th item, discarding the last m-1 items for each draw. | Class | com.numericalmethod.suanshu.stats.random.rng.univariate | SuanShu |
| UniformRNG | A pseudo uniform random number generator samples numbers from the unit interval, [0, 1], in such a way that there are equal probabilities of them falling in any same length sub-interval. | Class | com.numericalmethod.suanshu.stats.random.rng.univariate.uniform | SuanShu |
| UniformRNG .Method | the pseudo uniform random number generators availableMersenne Twister (recommended) | Class | com.numericalmethod.suanshu.stats.random.rng.univariate.uniform | SuanShu |
| VanDerWaerden1969 | Class | com.numericalmethod.suanshu.stats.random.rng.univariate.beta | SuanShu | |
| WeibullRNG | This random number generator samples from the Weibull distribution using the inverse transform sampling method. | Class | com.numericalmethod.suanshu.stats.random.rng.univariate | SuanShu |
| XiTanLiu2010a | Xi, Tan and Liu proposed two simple algorithms to generate gamma random numbers based on the ratio-of-uniforms method and logarithmic transformations of gamma random variable. | Class | com.numericalmethod.suanshu.stats.random.rng.univariate.gamma | SuanShu |
| XiTanLiu2010b | Xi, Tan and Liu proposed two simple algorithms to generate gamma random numbers based on the ratio-of-uniforms method and logarithmic transformations of gamma random variable. | Class | com.numericalmethod.suanshu.stats.random.rng.univariate.gamma | SuanShu |
| Ziggurat2000 | The Ziggurat algorithm is an algorithm for pseudo-random number sampling from the Normal distribution. | Class | com.numericalmethod.suanshu.stats.random.rng.univariate.normal | SuanShu |
| Ziggurat2000Exp | This implements the ziggurat algorithm to sample from the exponential distribution. | Class | com.numericalmethod.suanshu.stats.random.rng.univariate.exp | SuanShu |
| Zignor2005 | This is an improved version of the Ziggurat algorithm as proposed in the reference. | Class | com.numericalmethod.suanshu.stats.random.rng.univariate.normal | SuanShu |