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<div class="section" id="Random-Number-Generation">
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<span id="Random-Number-Generation-1"></span><h3 class="section">26.6 Random Number Generation</h3>
<p>Octave can generate random numbers from a large number of distributions. The
random number generators are based on the random number generators described in
<a href="Special-Utility-Matrices.html">Special Utility Matrices</a>.
</p>
<p>The following table summarizes the available random number generators (in
alphabetical order).
</p>
<table>
<thead><tr><th width="40%">Distribution</th><th width="30%">Function</th></tr></thead>
<tr><td width="40%">Univariate Discrete Distribution</td><td width="30%"><code>discrete_rnd</code></td></tr>
<tr><td width="40%">Empirical Distribution</td><td width="30%"><code>empirical_rnd</code></td></tr>
<tr><td width="40%">Exponential Distribution</td><td width="30%"><code>rande</code></td></tr>
<tr><td width="40%">Gamma Distribution</td><td width="30%"><code>randg</code></td></tr>
<tr><td width="40%">Poisson Distribution</td><td width="30%"><code>randp</code></td></tr>
<tr><td width="40%">Standard Normal Distribution</td><td width="30%"><code>randn</code></td></tr>
<tr><td width="40%">Uniform Distribution</td><td width="30%"><code>rand</code></td></tr>
<tr><td width="40%">Uniform Distribution (integers)</td><td width="30%"><code>randi</code></td></tr>
</table>
<span id="XREFdiscrete_005frnd"></span><dl class="def">
<dt id="index-discrete_005frnd"><span class="category">: </span><span><em></em> <strong>discrete_rnd</strong> <em>(<var>v</var>, <var>p</var>)</em><a href='#index-discrete_005frnd' class='copiable-anchor'> ¶</a></span></dt>
<dt id="index-discrete_005frnd-1"><span class="category">: </span><span><em></em> <strong>discrete_rnd</strong> <em>(<var>v</var>, <var>p</var>, <var>r</var>)</em><a href='#index-discrete_005frnd-1' class='copiable-anchor'> ¶</a></span></dt>
<dt id="index-discrete_005frnd-2"><span class="category">: </span><span><em></em> <strong>discrete_rnd</strong> <em>(<var>v</var>, <var>p</var>, <var>r</var>, <var>c</var>, …)</em><a href='#index-discrete_005frnd-2' class='copiable-anchor'> ¶</a></span></dt>
<dt id="index-discrete_005frnd-3"><span class="category">: </span><span><em></em> <strong>discrete_rnd</strong> <em>(<var>v</var>, <var>p</var>, [<var>sz</var>])</em><a href='#index-discrete_005frnd-3' class='copiable-anchor'> ¶</a></span></dt>
<dd><p>Return a matrix of random samples from the univariate distribution which
assumes the values in <var>v</var> with probabilities <var>p</var>.
</p>
<p>When called with a single size argument, return a square matrix with
the dimension specified. When called with more than one scalar argument the
first two arguments are taken as the number of rows and columns and any
further arguments specify additional matrix dimensions. The size may also
be specified with a vector of dimensions <var>sz</var>.
</p>
<p>If no size arguments are given then the result matrix is the common size of
<var>v</var> and <var>p</var>.
</p></dd></dl>
<span id="XREFempirical_005frnd"></span><dl class="def">
<dt id="index-empirical_005frnd"><span class="category">: </span><span><em></em> <strong>empirical_rnd</strong> <em>(<var>data</var>)</em><a href='#index-empirical_005frnd' class='copiable-anchor'> ¶</a></span></dt>
<dt id="index-empirical_005frnd-1"><span class="category">: </span><span><em></em> <strong>empirical_rnd</strong> <em>(<var>data</var>, <var>r</var>)</em><a href='#index-empirical_005frnd-1' class='copiable-anchor'> ¶</a></span></dt>
<dt id="index-empirical_005frnd-2"><span class="category">: </span><span><em></em> <strong>empirical_rnd</strong> <em>(<var>data</var>, <var>r</var>, <var>c</var>, …)</em><a href='#index-empirical_005frnd-2' class='copiable-anchor'> ¶</a></span></dt>
<dt id="index-empirical_005frnd-3"><span class="category">: </span><span><em></em> <strong>empirical_rnd</strong> <em>(<var>data</var>, [<var>sz</var>])</em><a href='#index-empirical_005frnd-3' class='copiable-anchor'> ¶</a></span></dt>
<dd><p>Return a matrix of random samples from the empirical distribution obtained
from the univariate sample <var>data</var>.
</p>
<p>When called with a single size argument, return a square matrix with
the dimension specified. When called with more than one scalar argument the
first two arguments are taken as the number of rows and columns and any
further arguments specify additional matrix dimensions. The size may also
be specified with a vector of dimensions <var>sz</var>.
</p>
<p>If no size arguments are given then the result matrix is a random ordering
of the sample <var>data</var>.
</p></dd></dl>
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