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.. | ||
arcsine | ||
bernoulli | ||
beta | ||
betaprime | ||
binomial | ||
box-muller | ||
cauchy | ||
chi | ||
chisquare | ||
cosine | ||
discrete-uniform | ||
docs/types | ||
erlang | ||
exponential | ||
f | ||
frechet | ||
gamma | ||
geometric | ||
gumbel | ||
hypergeometric | ||
improved-ziggurat | ||
invgamma | ||
kumaraswamy | ||
laplace | ||
levy | ||
lib | ||
logistic | ||
lognormal | ||
minstd | ||
minstd-shuffle | ||
mt19937 | ||
negative-binomial | ||
normal | ||
pareto-type1 | ||
poisson | ||
randi | ||
randn | ||
randu | ||
rayleigh | ||
t | ||
triangular | ||
uniform | ||
weibull | ||
package.json | ||
README.md |
Pseudorandom Number Generator Streams
Standard library pseudorandom number generator (PRNG) streams.
Usage
var ns = require( '@stdlib/random/streams' );
ns
Standard library pseudorandom number generator (PRNG) streams.
var streams = ns;
// returns {...}
The namespace contains the following functions for creating readable pseudorandom number generator streams:
arcsine( a, b[, options] )
: create a readable stream for generating pseudorandom numbers drawn from an arcsine distribution.bernoulli( p[, options] )
: create a readable stream for generating pseudorandom numbers drawn from a Bernoulli distribution.beta( alpha, beta[, options] )
: create a readable stream for generating pseudorandom numbers drawn from a beta distribution.betaprime( alpha, beta[, options] )
: create a readable stream for generating pseudorandom numbers drawn from a beta prime distribution.binomial( n, p[, options] )
: create a readable stream for generating pseudorandom numbers drawn from a binomial distribution.boxMuller( [options] )
: create a readable stream for generating pseudorandom numbers drawn from a standard normal distribution using the Box-Muller transform.cauchy( x0, gamma[, options] )
: create a readable stream for generating pseudorandom numbers drawn from a Cauchy distribution.chi( k[, options] )
: create a readable stream for generating pseudorandom numbers drawn from a chi distribution.chisquare( k[, options] )
: create a readable stream for generating pseudorandom numbers drawn from a chi-square distribution.cosine( mu, s[, options] )
: create a readable stream for generating pseudorandom numbers drawn from a raised cosine distribution.discreteUniform( a, b[, options] )
: create a readable stream for generating pseudorandom numbers drawn from a discrete uniform distribution.erlang( k, lambda[, options] )
: create a readable stream for generating pseudorandom numbers drawn from an Erlang distribution.exponential( lambda[, options] )
: create a readable stream for generating pseudorandom numbers drawn from an exponential distribution.f( d1, d2[, options] )
: create a readable stream for generating pseudorandom numbers drawn from an F distribution.frechet( alpha, s, m[, options] )
: create a readable stream for generating pseudorandom numbers drawn from a Fréchet distribution.gamma( alpha, beta[, options] )
: create a readable stream for generating pseudorandom numbers drawn from a gamma distribution.geometric( p[, options] )
: create a readable stream for generating pseudorandom numbers drawn from a geometric distribution.gumbel( mu, beta[, options] )
: create a readable stream for generating pseudorandom numbers drawn from a Gumbel distribution.hypergeometric( N, K, n[, options] )
: create a readable stream for generating pseudorandom numbers drawn from a hypergeometric distribution.improvedZiggurat( [options] )
: create a readable stream for generating pseudorandom numbers drawn from a standard normal distribution using the Improved Ziggurat algorithm.invgamma( alpha, beta[, options] )
: create a readable stream for generating pseudorandom numbers drawn from an inverse gamma distribution.kumaraswamy( a, b[, options] )
: create a readable stream for generating pseudorandom numbers drawn from a Kumaraswamy's double bounded distribution.laplace( mu, b[, options] )
: create a readable stream for generating pseudorandom numbers drawn from a Laplace (double exponential) distribution.levy( mu, c[, options] )
: create a readable stream for generating pseudorandom numbers drawn from a Lévy distribution.logistic( mu, s[, options] )
: create a readable stream for generating pseudorandom numbers drawn from a logistic distribution.lognormal( mu, sigma[, options] )
: create a readable stream for generating pseudorandom numbers drawn from a lognormal distribution.minstdShuffle( [options] )
: create a readable stream for a linear congruential pseudorandom number generator (LCG) whose output is shuffled.minstd( [options] )
: create a readable stream for a linear congruential pseudorandom number generator (LCG) based on Park and Miller.mt19937( [options] )
: create a readable stream for a 32-bit Mersenne Twister pseudorandom number generator.negativeBinomial( r, p[, options] )
: create a readable stream for generating pseudorandom numbers drawn from a negative binomial distribution.normal( mu, sigma[, options] )
: create a readable stream for generating pseudorandom numbers drawn from a normal distribution.pareto1( alpha, beta[, options] )
: create a readable stream for generating pseudorandom numbers drawn from a Pareto (Type I) distribution.poisson( lambda[, options] )
: create a readable stream for generating pseudorandom numbers drawn from a Poisson distribution.randi( [options] )
: create a readable stream for generating pseudorandom numbers having integer values.randn( [options] )
: create a readable stream for generating pseudorandom numbers drawn from a standard normal distribution.randu( [options] )
: create a readable stream for generating uniformly distributed pseudorandom numbers between0
and1
.rayleigh( sigma[, options] )
: create a readable stream for generating pseudorandom numbers drawn from a Rayleigh distribution.t( v[, options] )
: create a readable stream for generating pseudorandom numbers drawn from a Student's t distribution.triangular( a, b, c[, options] )
: create a readable stream for generating pseudorandom numbers drawn from a triangular distribution.uniform( a, b[, options] )
: create a readable stream for generating pseudorandom numbers drawn from a uniform distribution.weibull( k, lambda[, options] )
: create a readable stream for generating pseudorandom numbers drawn from a Weibull distribution.
Examples
var objectKeys = require( '@stdlib/utils/keys' );
var ns = require( '@stdlib/random/streams' );
console.log( objectKeys( ns ) );