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@@ -1 +1 @@
-Copyright (c) 2016-2023 The Stdlib Authors.
+Copyright (c) 2016-2024 The Stdlib Authors.

array/README.md

@@ -46,20 +46,26 @@ The namespace contains the following:
 <div class="namespace-toc">
 
 -   <span class="signature">[`arcsine( len, a, b[, options] )`][@stdlib/random/array/arcsine]</span><span class="delimiter">: </span><span class="description">create an array containing pseudorandom numbers drawn from an arcsine distribution.</span>
+-   <span class="signature">[`bernoulli( len, p[, options] )`][@stdlib/random/array/bernoulli]</span><span class="delimiter">: </span><span class="description">create an array containing pseudorandom numbers drawn from a Bernoulli distribution.</span>
 -   <span class="signature">[`beta( len, alpha, beta[, options] )`][@stdlib/random/array/beta]</span><span class="delimiter">: </span><span class="description">create an array containing pseudorandom numbers drawn from a beta distribution.</span>
 -   <span class="signature">[`betaprime( len, alpha, beta[, options] )`][@stdlib/random/array/betaprime]</span><span class="delimiter">: </span><span class="description">create an array containing pseudorandom numbers drawn from a beta prime distribution.</span>
+-   <span class="signature">[`chi( len, k[, options] )`][@stdlib/random/array/chi]</span><span class="delimiter">: </span><span class="description">create an array containing pseudorandom numbers drawn from a chi distribution.</span>
+-   <span class="signature">[`chisquare( len, k[, options] )`][@stdlib/random/array/chisquare]</span><span class="delimiter">: </span><span class="description">create an array containing pseudorandom numbers drawn from a chi-square distribution.</span>
 -   <span class="signature">[`cosine( len, mu, s[, options] )`][@stdlib/random/array/cosine]</span><span class="delimiter">: </span><span class="description">create an array containing pseudorandom numbers drawn from a raised cosine distribution.</span>
 -   <span class="signature">[`discreteUniform( len, a, b[, options] )`][@stdlib/random/array/discrete-uniform]</span><span class="delimiter">: </span><span class="description">create an array containing pseudorandom numbers drawn from a discrete uniform distribution.</span>
 -   <span class="signature">[`exponential( len, lambda[, options] )`][@stdlib/random/array/exponential]</span><span class="delimiter">: </span><span class="description">create an array containing pseudorandom numbers drawn from an exponential distribution.</span>
 -   <span class="signature">[`gamma( len, alpha, beta[, options] )`][@stdlib/random/array/gamma]</span><span class="delimiter">: </span><span class="description">create an array containing pseudorandom numbers drawn from a gamma distribution.</span>
--   <span class="signature">[`geometric( len, p[, options] )`][@stdlib/random/array/geometric]</span><span class="delimiter">: </span><span class="description">create an array containing pseudorandom numbers drawn from an geometric distribution.</span>
+-   <span class="signature">[`geometric( len, p[, options] )`][@stdlib/random/array/geometric]</span><span class="delimiter">: </span><span class="description">create an array containing pseudorandom numbers drawn from a geometric distribution.</span>
 -   <span class="signature">[`invgamma( len, alpha, beta[, options] )`][@stdlib/random/array/invgamma]</span><span class="delimiter">: </span><span class="description">create an array containing pseudorandom numbers drawn from an inverse gamma distribution.</span>
 -   <span class="signature">[`lognormal( len, mu, sigma[, options] )`][@stdlib/random/array/lognormal]</span><span class="delimiter">: </span><span class="description">create an array containing pseudorandom numbers drawn from a lognormal distribution.</span>
 -   <span class="signature">[`minstdShuffle( len[, options] )`][@stdlib/random/array/minstd-shuffle]</span><span class="delimiter">: </span><span class="description">create an array containing pseudorandom numbers generated using a linear congruential pseudorandom number generator (LCG) whose output is shuffled.</span>
 -   <span class="signature">[`minstd( len[, options] )`][@stdlib/random/array/minstd]</span><span class="delimiter">: </span><span class="description">create an array containing pseudorandom numbers generated using a linear congruential pseudorandom number generator (LCG).</span>
 -   <span class="signature">[`mt19937( len[, options] )`][@stdlib/random/array/mt19937]</span><span class="delimiter">: </span><span class="description">create an array containing pseudorandom numbers generated using a 32-bit Mersenne Twister pseudorandom number generator.</span>
 -   <span class="signature">[`normal( len, mu, sigma[, options] )`][@stdlib/random/array/normal]</span><span class="delimiter">: </span><span class="description">create an array containing pseudorandom numbers drawn from a normal distribution.</span>
+-   <span class="signature">[`poisson( len, lambda[, options] )`][@stdlib/random/array/poisson]</span><span class="delimiter">: </span><span class="description">create an array containing pseudorandom numbers drawn from a Poisson distribution.</span>
 -   <span class="signature">[`randu( len[, options] )`][@stdlib/random/array/randu]</span><span class="delimiter">: </span><span class="description">create an array containing uniformly distributed pseudorandom numbers between `0` and `1`.</span>
+-   <span class="signature">[`rayleigh( len, sigma[, options] )`][@stdlib/random/array/rayleigh]</span><span class="delimiter">: </span><span class="description">create an array containing pseudorandom numbers drawn from a Rayleigh distribution.</span>
+-   <span class="signature">[`t( len, v[, options] )`][@stdlib/random/array/t]</span><span class="delimiter">: </span><span class="description">create an array containing pseudorandom numbers drawn from a Student's t-distribution.</span>
 -   <span class="signature">[`uniform( len, a, b[, options] )`][@stdlib/random/array/uniform]</span><span class="delimiter">: </span><span class="description">create an array containing pseudorandom numbers drawn from a continuous uniform distribution.</span>
 
 </div>
@@ -105,10 +111,16 @@ console.log( objectKeys( ns ) );
 
 [@stdlib/random/array/arcsine]: https://github.com/stdlib-js/random/tree/main/array/arcsine
 
+[@stdlib/random/array/bernoulli]: https://github.com/stdlib-js/random/tree/main/array/bernoulli
+
 [@stdlib/random/array/beta]: https://github.com/stdlib-js/random/tree/main/array/beta
 
 [@stdlib/random/array/betaprime]: https://github.com/stdlib-js/random/tree/main/array/betaprime
 
+[@stdlib/random/array/chi]: https://github.com/stdlib-js/random/tree/main/array/chi
+
+[@stdlib/random/array/chisquare]: https://github.com/stdlib-js/random/tree/main/array/chisquare
+
 [@stdlib/random/array/cosine]: https://github.com/stdlib-js/random/tree/main/array/cosine
 
 [@stdlib/random/array/discrete-uniform]: https://github.com/stdlib-js/random/tree/main/array/discrete-uniform
@@ -131,8 +143,14 @@ console.log( objectKeys( ns ) );
 
 [@stdlib/random/array/normal]: https://github.com/stdlib-js/random/tree/main/array/normal
 
+[@stdlib/random/array/poisson]: https://github.com/stdlib-js/random/tree/main/array/poisson
+
 [@stdlib/random/array/randu]: https://github.com/stdlib-js/random/tree/main/array/randu
 
+[@stdlib/random/array/rayleigh]: https://github.com/stdlib-js/random/tree/main/array/rayleigh
+
+[@stdlib/random/array/t]: https://github.com/stdlib-js/random/tree/main/array/t
+
 [@stdlib/random/array/uniform]: https://github.com/stdlib-js/random/tree/main/array/uniform
 
 <!-- </toc-links> -->