Array

Pseudorandom number generator (PRNG) array creation functions.

Usage

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

ns

Namespace containing array creation pseudorandom number generator (PRNG) functions.

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

The namespace contains the following:

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

Examples

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

console.log( objectKeys( ns ) );