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<li class="navelem"><a class="el" href="namespace_quant_lib.html">QuantLib</a></li><li class="navelem"><a class="el" href="class_quant_lib_1_1_inverse_cumulative_normal.html">InverseCumulativeNormal</a></li> </ul>
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<div class="title">InverseCumulativeNormal Class Reference</div> </div>
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<p>Inverse cumulative normal distribution function.
<a href="class_quant_lib_1_1_inverse_cumulative_normal.html#details">More...</a></p>
<p><code>#include <ql/math/distributions/normaldistribution.hpp></code></p>
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typedef <a class="el" href="group__types.html#ga4bdf4bfe76b9ffa6fa64c47d8bfa0c78">Real</a> </td><td class="memItemRight" valign="bottom"><b>argument_type</b></td></tr>
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typedef <a class="el" href="group__types.html#ga4bdf4bfe76b9ffa6fa64c47d8bfa0c78">Real</a> </td><td class="memItemRight" valign="bottom"><b>result_type</b></td></tr>
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 </td><td class="memItemRight" valign="bottom"><b>InverseCumulativeNormal</b> (<a class="el" href="group__types.html#ga4bdf4bfe76b9ffa6fa64c47d8bfa0c78">Real</a> average=0.0, <a class="el" href="group__types.html#ga4bdf4bfe76b9ffa6fa64c47d8bfa0c78">Real</a> sigma=1.0)</td></tr>
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<a class="el" href="group__types.html#ga4bdf4bfe76b9ffa6fa64c47d8bfa0c78">Real</a> </td><td class="memItemRight" valign="bottom"><b>operator()</b> (<a class="el" href="group__types.html#ga4bdf4bfe76b9ffa6fa64c47d8bfa0c78">Real</a> x) const</td></tr>
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static <a class="el" href="group__types.html#ga4bdf4bfe76b9ffa6fa64c47d8bfa0c78">Real</a> </td><td class="memItemRight" valign="bottom"><b>standard_value</b> (<a class="el" href="group__types.html#ga4bdf4bfe76b9ffa6fa64c47d8bfa0c78">Real</a> x)</td></tr>
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<a name="details" id="details"></a><h2 class="groupheader">Detailed Description</h2>
<div class="textblock"><p>Inverse cumulative normal distribution function. </p>
<p>Given x between zero and one as the integral value of a gaussian normal distribution this class provides the value y such that formula here ...</p>
<p>It use Acklam's approximation: by Peter J. Acklam, University of Oslo, Statistics Division. URL: <a href="http://home.online.no/~pjacklam/notes/invnorm/index.html">http://home.online.no/~pjacklam/notes/invnorm/index.html</a></p>
<p>This class can also be used to generate a gaussian normal distribution from a uniform distribution. This is especially useful when a gaussian normal distribution is generated from a low discrepancy uniform distribution: in this case the traditional Box-Muller approach and its variants would not preserve the sequence's low-discrepancy. </p>
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