time-to-botec/squiggle/node_modules/@stdlib/random/iter/README.md

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# Pseudorandom Number Generator Iterators

> Standard library pseudorandom number generator (PRNG) iterators.

<section class="usage">

## 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:

<!-- <toc pattern="*"> -->

<div class="namespace-toc">

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

</div>

<!-- </toc> -->

</section>

<!-- /.usage -->

<section class="examples">

## Examples

<!-- TODO: better examples -->

<!-- eslint no-undef: "error" -->

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

console.log( objectKeys( ns ) );
```

</section>

<!-- /.examples -->

<section class="links">

<!-- <toc-links> -->

[@stdlib/random/iter/arcsine]: https://www.npmjs.com/package/@stdlib/random/tree/main/iter/arcsine

[@stdlib/random/iter/bernoulli]: https://www.npmjs.com/package/@stdlib/random/tree/main/iter/bernoulli

[@stdlib/random/iter/beta]: https://www.npmjs.com/package/@stdlib/random/tree/main/iter/beta

[@stdlib/random/iter/betaprime]: https://www.npmjs.com/package/@stdlib/random/tree/main/iter/betaprime

[@stdlib/random/iter/binomial]: https://www.npmjs.com/package/@stdlib/random/tree/main/iter/binomial

[@stdlib/random/iter/box-muller]: https://www.npmjs.com/package/@stdlib/random/tree/main/iter/box-muller

[@stdlib/random/iter/cauchy]: https://www.npmjs.com/package/@stdlib/random/tree/main/iter/cauchy

[@stdlib/random/iter/chi]: https://www.npmjs.com/package/@stdlib/random/tree/main/iter/chi

[@stdlib/random/iter/chisquare]: https://www.npmjs.com/package/@stdlib/random/tree/main/iter/chisquare

[@stdlib/random/iter/cosine]: https://www.npmjs.com/package/@stdlib/random/tree/main/iter/cosine

[@stdlib/random/iter/discrete-uniform]: https://www.npmjs.com/package/@stdlib/random/tree/main/iter/discrete-uniform

[@stdlib/random/iter/erlang]: https://www.npmjs.com/package/@stdlib/random/tree/main/iter/erlang

[@stdlib/random/iter/exponential]: https://www.npmjs.com/package/@stdlib/random/tree/main/iter/exponential

[@stdlib/random/iter/f]: https://www.npmjs.com/package/@stdlib/random/tree/main/iter/f

[@stdlib/random/iter/frechet]: https://www.npmjs.com/package/@stdlib/random/tree/main/iter/frechet

[@stdlib/random/iter/gamma]: https://www.npmjs.com/package/@stdlib/random/tree/main/iter/gamma

[@stdlib/random/iter/geometric]: https://www.npmjs.com/package/@stdlib/random/tree/main/iter/geometric

[@stdlib/random/iter/gumbel]: https://www.npmjs.com/package/@stdlib/random/tree/main/iter/gumbel

[@stdlib/random/iter/hypergeometric]: https://www.npmjs.com/package/@stdlib/random/tree/main/iter/hypergeometric

[@stdlib/random/iter/improved-ziggurat]: https://www.npmjs.com/package/@stdlib/random/tree/main/iter/improved-ziggurat

[@stdlib/random/iter/invgamma]: https://www.npmjs.com/package/@stdlib/random/tree/main/iter/invgamma

[@stdlib/random/iter/kumaraswamy]: https://www.npmjs.com/package/@stdlib/random/tree/main/iter/kumaraswamy

[@stdlib/random/iter/laplace]: https://www.npmjs.com/package/@stdlib/random/tree/main/iter/laplace

[@stdlib/random/iter/levy]: https://www.npmjs.com/package/@stdlib/random/tree/main/iter/levy

[@stdlib/random/iter/logistic]: https://www.npmjs.com/package/@stdlib/random/tree/main/iter/logistic

[@stdlib/random/iter/lognormal]: https://www.npmjs.com/package/@stdlib/random/tree/main/iter/lognormal

[@stdlib/random/iter/minstd-shuffle]: https://www.npmjs.com/package/@stdlib/random/tree/main/iter/minstd-shuffle

[@stdlib/random/iter/minstd]: https://www.npmjs.com/package/@stdlib/random/tree/main/iter/minstd

[@stdlib/random/iter/mt19937]: https://www.npmjs.com/package/@stdlib/random/tree/main/iter/mt19937

[@stdlib/random/iter/negative-binomial]: https://www.npmjs.com/package/@stdlib/random/tree/main/iter/negative-binomial

[@stdlib/random/iter/normal]: https://www.npmjs.com/package/@stdlib/random/tree/main/iter/normal

[@stdlib/random/iter/pareto-type1]: https://www.npmjs.com/package/@stdlib/random/tree/main/iter/pareto-type1

[@stdlib/random/iter/poisson]: https://www.npmjs.com/package/@stdlib/random/tree/main/iter/poisson

[@stdlib/random/iter/randi]: https://www.npmjs.com/package/@stdlib/random/tree/main/iter/randi

[@stdlib/random/iter/randn]: https://www.npmjs.com/package/@stdlib/random/tree/main/iter/randn

[@stdlib/random/iter/randu]: https://www.npmjs.com/package/@stdlib/random/tree/main/iter/randu

[@stdlib/random/iter/rayleigh]: https://www.npmjs.com/package/@stdlib/random/tree/main/iter/rayleigh

[@stdlib/random/iter/t]: https://www.npmjs.com/package/@stdlib/random/tree/main/iter/t

[@stdlib/random/iter/triangular]: https://www.npmjs.com/package/@stdlib/random/tree/main/iter/triangular

[@stdlib/random/iter/uniform]: https://www.npmjs.com/package/@stdlib/random/tree/main/iter/uniform

[@stdlib/random/iter/weibull]: https://www.npmjs.com/package/@stdlib/random/tree/main/iter/weibull

<!-- </toc-links> -->

</section>

<!-- /.links -->