Pseudorandom Number Generator Iterators

Pseudorandom number generator (PRNG) iterators.

Installation

npm install @stdlib/random-iter

Usage

var ns = require( '@stdlib/random-iter' );

ns

Namespace containing pseudorandom number generator (PRNG) iterators.

var iterators = ns;
// returns {...}

The namespace contains the following functions for creating iterator protocol-compliant iterators:

• arcsine( a, b[, options] ): create an iterator for generating pseudorandom numbers drawn from an arcsine distribution.
• bernoulli( p[, options] ): create an iterator for generating pseudorandom numbers drawn from a Bernoulli distribution.
• beta( alpha, beta[, options] ): create an iterator for generating pseudorandom numbers drawn from a beta distribution.
• betaprime( alpha, beta[, options] ): create an iterator for generating pseudorandom numbers drawn from a beta prime distribution.
• binomial( n, p[, options] ): create an iterator for generating pseudorandom numbers drawn from a binomial distribution.
• boxMuller( [options] ): create an iterator for generating pseudorandom numbers drawn from a standard normal distribution using the Box-Muller transform.
• cauchy( x0, gamma[, options] ): create an iterator for generating pseudorandom numbers drawn from a Cauchy distribution.
• chi( k[, options] ): create an iterator for generating pseudorandom numbers drawn from a chi distribution.
• chisquare( k[, options] ): create an iterator for generating pseudorandom numbers drawn from a chi-square distribution.
• cosine( mu, s[, options] ): create an iterator for generating pseudorandom numbers drawn from a raised cosine distribution.
• discreteUniform( a, b[, options] ): create an iterator for generating pseudorandom numbers drawn from a discrete uniform distribution.
• erlang( k, lambda[, options] ): create an iterator for generating pseudorandom numbers drawn from an Erlang distribution.
• exponential( lambda[, options] ): create an iterator for generating pseudorandom numbers drawn from an exponential distribution.
• f( d1, d2[, options] ): create an iterator for generating pseudorandom numbers drawn from an F distribution.
• frechet( alpha, s, m[, options] ): create an iterator for generating pseudorandom numbers drawn from a Fréchet distribution.
• gamma( alpha, beta[, options] ): create an iterator for generating pseudorandom numbers drawn from a gamma distribution.
• geometric( p[, options] ): create an iterator for generating pseudorandom numbers drawn from a geometric distribution.
• gumbel( mu, beta[, options] ): create an iterator for generating pseudorandom numbers drawn from a Gumbel distribution.
• hypergeometric( N, K, n[, options] ): create an iterator for generating pseudorandom numbers drawn from a hypergeometric distribution.
• improvedZiggurat( [options] ): create an iterator for generating pseudorandom numbers drawn from a standard normal distribution using the Improved Ziggurat algorithm.
• invgamma( alpha, beta[, options] ): create an iterator for generating pseudorandom numbers drawn from an inverse gamma distribution.
• kumaraswamy( a, b[, options] ): create an iterator for generating pseudorandom numbers drawn from a Kumaraswamy's double bounded distribution.
• laplace( mu, b[, options] ): create an iterator for generating pseudorandom numbers drawn from a Laplace (double exponential) distribution.
• levy( mu, c[, options] ): create an iterator for generating pseudorandom numbers drawn from a Lévy distribution.
• logistic( mu, s[, options] ): create an iterator for generating pseudorandom numbers drawn from a logistic distribution.
• lognormal( mu, sigma[, options] ): create an iterator for generating pseudorandom numbers drawn from a lognormal distribution.
• minstdShuffle( [options] ): create an iterator for a linear congruential pseudorandom number generator (LCG) whose output is shuffled.
• minstd( [options] ): create an iterator for a linear congruential pseudorandom number generator (LCG) based on Park and Miller.
• mt19937( [options] ): create an iterator for a 32-bit Mersenne Twister pseudorandom number generator.
• negativeBinomial( r, p[, options] ): create an iterator for generating pseudorandom numbers drawn from a negative binomial distribution.
• normal( mu, sigma[, options] ): create an iterator for generating pseudorandom numbers drawn from a normal distribution.
• pareto1( alpha, beta[, options] ): create an iterator for generating pseudorandom numbers drawn from a Pareto (Type I) distribution.
• poisson( lambda[, options] ): create an iterator for generating pseudorandom numbers drawn from a Poisson distribution.
• randi( [options] ): create an iterator for generating pseudorandom numbers having integer values.
• randn( [options] ): create an iterator for generating pseudorandom numbers drawn from a standard normal distribution.
• randu( [options] ): create an iterator for generating uniformly distributed pseudorandom numbers between 0 and 1.
• rayleigh( sigma[, options] ): create an iterator for generating pseudorandom numbers drawn from a Rayleigh distribution.
• t( v[, options] ): create an iterator for generating pseudorandom numbers drawn from a Student's t distribution.
• triangular( a, b, c[, options] ): create an iterator for generating pseudorandom numbers drawn from a triangular distribution.
• uniform( a, b[, options] ): create an iterator for generating pseudorandom numbers drawn from a continuous uniform distribution.
• weibull( k, lambda[, options] ): create an iterator for generating pseudorandom numbers drawn from a Weibull distribution.

Examples

var objectKeys = require( '@stdlib/utils-keys' );
var ns = require( '@stdlib/random-iter' );

console.log( objectKeys( ns ) );

Notice

This package is part of stdlib, a standard library for JavaScript and Node.js, with an emphasis on numerical and scientific computing. The library provides a collection of robust, high performance libraries for mathematics, statistics, streams, utilities, and more.

For more information on the project, filing bug reports and feature requests, and guidance on how to develop stdlib, see the main project repository.

Community

License

See LICENSE.

Copyright

Copyright © 2016-2024. The Stdlib Authors.