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<a name="The-Logarithmic-Distribution"></a>
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<p>
Next: <a href="Shuffling-and-Sampling.html#Shuffling-and-Sampling" accesskey="n" rel="next">Shuffling and Sampling</a>, Previous: <a href="The-Hypergeometric-Distribution.html#The-Hypergeometric-Distribution" accesskey="p" rel="previous">The Hypergeometric Distribution</a>, Up: <a href="Random-Number-Distributions.html#Random-Number-Distributions" accesskey="u" rel="up">Random Number Distributions</a> &nbsp; [<a href="Function-Index.html#Function-Index" title="Index" rel="index">Index</a>]</p>
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<a name="The-Logarithmic-Distribution-1"></a>
<h3 class="section">20.38 The Logarithmic Distribution</h3>
<dl>
<dt><a name="index-gsl_005fran_005flogarithmic"></a>Function: <em>unsigned int</em> <strong>gsl_ran_logarithmic</strong> <em>(const gsl_rng * <var>r</var>, double <var>p</var>)</em></dt>
<dd><a name="index-Logarithmic-random-variates"></a>
<p>This function returns a random integer from the logarithmic
distribution.  The probability distribution for logarithmic random variates
is,
</p>
<div class="example">
<pre class="example">p(k) = {-1 \over \log(1-p)} {(p^k \over k)}
</pre></div>

<p>for <em>k &gt;= 1</em>.
</p></dd></dl>

<dl>
<dt><a name="index-gsl_005fran_005flogarithmic_005fpdf"></a>Function: <em>double</em> <strong>gsl_ran_logarithmic_pdf</strong> <em>(unsigned int <var>k</var>, double <var>p</var>)</em></dt>
<dd><p>This function computes the probability <em>p(k)</em> of obtaining <var>k</var>
from a logarithmic distribution with probability parameter <var>p</var>,
using the formula given above.
</p></dd></dl>

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