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Pseudorandom number generator (PRNG) strided array functions.
npm install @stdlib/random-stridedAlternatively,
- To load the package in a website via a
scripttag without installation and bundlers, use the ES Module available on theesmbranch (see README). - If you are using Deno, visit the
denobranch (see README for usage intructions). - For use in Observable, or in browser/node environments, use the Universal Module Definition (UMD) build available on the
umdbranch (see README).
The branches.md file summarizes the available branches and displays a diagram illustrating their relationships.
To view installation and usage instructions specific to each branch build, be sure to explicitly navigate to the respective README files on each branch, as linked to above.
var ns = require( '@stdlib/random-strided' );Namespace containing strided array pseudorandom number generator (PRNG) functions.
var o = ns;
// returns {...}The namespace contains the following:
arcsine( N, a, sa, b, sb, out, so[, options] ): fill a strided array with pseudorandom numbers drawn from an arcsine distribution.bernoulli( N, p, sp, out, so ): fill a strided array with pseudorandom numbers drawn from a Bernoulli distribution.beta( N, alpha, sa, beta, sb, out, so[, options] ): fill a strided array with pseudorandom numbers drawn from a beta distribution.betaprime( N, alpha, sa, beta, sb, out, so[, options] ): fill a strided array with pseudorandom numbers drawn from a beta prime distribution.chi( N, k, sk, out, so ): fill a strided array with pseudorandom numbers drawn from a chi distribution.chisquare( N, k, sk, out, so ): fill a strided array with pseudorandom numbers drawn from a chi-square distribution.cosine( N, mu, sm, s, ss, out, so[, options] ): fill a strided array with pseudorandom numbers drawn from a raised cosine distribution.discreteUniform( N, a, sa, b, sb, out, so[, options] ): fill a strided array with pseudorandom numbers drawn from a discrete uniform distribution.exponential( N, lambda, sl, out, so ): fill a strided array with pseudorandom numbers drawn from an exponential distribution.gamma( N, alpha, sa, beta, sb, out, so[, options] ): fill a strided array with pseudorandom numbers drawn from a gamma distribution.geometric( N, p, sp, out, so ): fill a strided array with pseudorandom numbers drawn from a geometric distribution.invgamma( N, alpha, sa, beta, sb, out, so[, options] ): fill a strided array with pseudorandom numbers drawn from an inverse gamma distribution.lognormal( N, mu, sm, sigma, ss, out, so[, options] ): fill a strided array with pseudorandom numbers drawn from a lognormal distribution.minstdShuffle( N, out, so[, options] ): fill a strided array with pseudorandom numbers generated using a linear congruential pseudorandom number generator (LCG) whose output is shuffled.minstd( N, out, so[, options] ): fill a strided array with pseudorandom numbers generated using a linear congruential pseudorandom number generator (LCG).mt19937( N, out, so[, options] ): fill a strided array with pseudorandom numbers generated using a 32-bit Mersenne Twister pseudorandom number generator.normal( N, mu, sm, sigma, ss, out, so[, options] ): fill a strided array with pseudorandom numbers drawn from a normal distribution.poisson( N, lambda, sl, out, so ): fill a strided array with pseudorandom numbers drawn from a Poisson distribution.randu( N, out, so[, options] ): fill a strided array with uniformly distributed pseudorandom numbers between0and1.rayleigh( N, sigma, ss, out, so ): fill a strided array with pseudorandom numbers drawn from a Rayleigh distribution.t( N, v, sv, out, so ): fill a strided array with pseudorandom numbers drawn from a Student's t-distribution.uniform( N, a, sa, b, sb, out, so[, options] ): fill a strided array with pseudorandom numbers drawn from a continuous uniform distribution.weibull( N, k, sk, lambda, sl, out, so[, options] ): fill a strided array with pseudorandom numbers drawn from a Weibull distribution.
var objectKeys = require( '@stdlib/utils-keys' );
var ns = require( '@stdlib/random-strided' );
console.log( objectKeys( ns ) );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.
See LICENSE.
Copyright © 2016-2024. The Stdlib Authors.
