## Usage
```javascript
var ns = require( '@stdlib/random/iter' );
```
#### ns
Standard library pseudorandom number generator (PRNG) iterators.
```javascript
var iterators = ns;
// returns {...}
```
The namespace contains the following functions for creating iterator protocol-compliant iterators:
- [`arcsine( a, b[, options] )`][@stdlib/random/iter/arcsine]: create an iterator for generating pseudorandom numbers drawn from an arcsine distribution.
- [`bernoulli( p[, options] )`][@stdlib/random/iter/bernoulli]: create an iterator for generating pseudorandom numbers drawn from a Bernoulli distribution.
- [`beta( alpha, beta[, options] )`][@stdlib/random/iter/beta]: create an iterator for generating pseudorandom numbers drawn from a beta distribution.
- [`betaprime( alpha, beta[, options] )`][@stdlib/random/iter/betaprime]: create an iterator for generating pseudorandom numbers drawn from a beta prime distribution.
- [`binomial( n, p[, options] )`][@stdlib/random/iter/binomial]: create an iterator for generating pseudorandom numbers drawn from a binomial distribution.
- [`boxMuller( [options] )`][@stdlib/random/iter/box-muller]: create an iterator for generating pseudorandom numbers drawn from a standard normal distribution using the Box-Muller transform.
- [`cauchy( x0, gamma[, options] )`][@stdlib/random/iter/cauchy]: create an iterator for generating pseudorandom numbers drawn from a Cauchy distribution.
- [`chi( k[, options] )`][@stdlib/random/iter/chi]: create an iterator for generating pseudorandom numbers drawn from a chi distribution.
- [`chisquare( k[, options] )`][@stdlib/random/iter/chisquare]: create an iterator for generating pseudorandom numbers drawn from a chi-square distribution.
- [`cosine( mu, s[, options] )`][@stdlib/random/iter/cosine]: create an iterator for generating pseudorandom numbers drawn from a raised cosine distribution.
- [`discreteUniform( a, b[, options] )`][@stdlib/random/iter/discrete-uniform]: create an iterator for generating pseudorandom numbers drawn from a discrete uniform distribution.
- [`erlang( k, lambda[, options] )`][@stdlib/random/iter/erlang]: create an iterator for generating pseudorandom numbers drawn from an Erlang distribution.
- [`exponential( lambda[, options] )`][@stdlib/random/iter/exponential]: create an iterator for generating pseudorandom numbers drawn from an exponential distribution.
- [`f( d1, d2[, options] )`][@stdlib/random/iter/f]: create an iterator for generating pseudorandom numbers drawn from an F distribution.
- [`frechet( alpha, s, m[, options] )`][@stdlib/random/iter/frechet]: create an iterator for generating pseudorandom numbers drawn from a Fréchet distribution.
- [`gamma( alpha, beta[, options] )`][@stdlib/random/iter/gamma]: create an iterator for generating pseudorandom numbers drawn from a gamma distribution.
- [`geometric( p[, options] )`][@stdlib/random/iter/geometric]: create an iterator for generating pseudorandom numbers drawn from a geometric distribution.
- [`gumbel( mu, beta[, options] )`][@stdlib/random/iter/gumbel]: create an iterator for generating pseudorandom numbers drawn from a Gumbel distribution.
- [`hypergeometric( N, K, n[, options] )`][@stdlib/random/iter/hypergeometric]: create an iterator for generating pseudorandom numbers drawn from a hypergeometric distribution.
- [`improvedZiggurat( [options] )`][@stdlib/random/iter/improved-ziggurat]: create an iterator for generating pseudorandom numbers drawn from a standard normal distribution using the Improved Ziggurat algorithm.
- [`invgamma( alpha, beta[, options] )`][@stdlib/random/iter/invgamma]: create an iterator for generating pseudorandom numbers drawn from an inverse gamma distribution.
- [`kumaraswamy( a, b[, options] )`][@stdlib/random/iter/kumaraswamy]: create an iterator for generating pseudorandom numbers drawn from a Kumaraswamy's double bounded distribution.
- [`laplace( mu, b[, options] )`][@stdlib/random/iter/laplace]: create an iterator for generating pseudorandom numbers drawn from a Laplace (double exponential) distribution.
- [`levy( mu, c[, options] )`][@stdlib/random/iter/levy]: create an iterator for generating pseudorandom numbers drawn from a Lévy distribution.
- [`logistic( mu, s[, options] )`][@stdlib/random/iter/logistic]: create an iterator for generating pseudorandom numbers drawn from a logistic distribution.
- [`lognormal( mu, sigma[, options] )`][@stdlib/random/iter/lognormal]: create an iterator for generating pseudorandom numbers drawn from a lognormal distribution.
- [`minstdShuffle( [options] )`][@stdlib/random/iter/minstd-shuffle]: create an iterator for a linear congruential pseudorandom number generator (LCG) whose output is shuffled.
- [`minstd( [options] )`][@stdlib/random/iter/minstd]: create an iterator for a linear congruential pseudorandom number generator (LCG) based on Park and Miller.
- [`mt19937( [options] )`][@stdlib/random/iter/mt19937]: create an iterator for a 32-bit Mersenne Twister pseudorandom number generator.
- [`negativeBinomial( r, p[, options] )`][@stdlib/random/iter/negative-binomial]: create an iterator for generating pseudorandom numbers drawn from a negative binomial distribution.
- [`normal( mu, sigma[, options] )`][@stdlib/random/iter/normal]: create an iterator for generating pseudorandom numbers drawn from a normal distribution.
- [`pareto1( alpha, beta[, options] )`][@stdlib/random/iter/pareto-type1]: create an iterator for generating pseudorandom numbers drawn from a Pareto (Type I) distribution.
- [`poisson( lambda[, options] )`][@stdlib/random/iter/poisson]: create an iterator for generating pseudorandom numbers drawn from a Poisson distribution.
- [`randi( [options] )`][@stdlib/random/iter/randi]: create an iterator for generating pseudorandom numbers having integer values.
- [`randn( [options] )`][@stdlib/random/iter/randn]: create an iterator for generating pseudorandom numbers drawn from a standard normal distribution.
- [`randu( [options] )`][@stdlib/random/iter/randu]: create an iterator for generating uniformly distributed pseudorandom numbers between `0` and `1`.
- [`rayleigh( sigma[, options] )`][@stdlib/random/iter/rayleigh]: create an iterator for generating pseudorandom numbers drawn from a Rayleigh distribution.
- [`t( v[, options] )`][@stdlib/random/iter/t]: create an iterator for generating pseudorandom numbers drawn from a Student's t distribution.
- [`triangular( a, b, c[, options] )`][@stdlib/random/iter/triangular]: create an iterator for generating pseudorandom numbers drawn from a triangular distribution.
- [`uniform( a, b[, options] )`][@stdlib/random/iter/uniform]: create an iterator for generating pseudorandom numbers drawn from a continuous uniform distribution.
- [`weibull( k, lambda[, options] )`][@stdlib/random/iter/weibull]: create an iterator for generating pseudorandom numbers drawn from a Weibull distribution.