<html><head><title>Distributions de nombres aléatoires de la librairie GSL</title><link rel="stylesheet" href="common/kde-default.css" type="text/css"><meta name="generator" content="DocBook XSL Stylesheets V1.48"><meta name="keywords" content="KDE, LabPlot, plot"><meta http-equiv="Content-Type" content="text/html; charset=iso-8859-15"><meta name="GENERATOR" content="KDE XSL Stylesheet V1.13 using libxslt"><link rel="home" href="index.html" title="Manuel d'utilisation de LabPlot"><link rel="up" href="parser.html" title="Chapitre 7. Répertoire de Fonctions"><link rel="previous" href="parser-gsl.html" title="Fonctions Spéciales de la librairie GSL"><link rel="next" href="parser-const.html" title="Constantes"></head><body bgcolor="white" text="black" link="#0000FF" vlink="#840084" alink="#0000FF"><table border="0" cellpadding="0" cellspacing="0" width="100%"><tr class="header"><td colspan="2"> </td></tr><tr id="logo"><td valign="top"><img src="common/kde_logo.png" alt="KDE - The K Desktop Environment" width="296" height="79" border="0"></td><td valign="middle" align="center" id="location"><h1>Distributions de nombres aléatoires de la librairie GSL</h1></td></tr></table><table width="100%" class="header"><tbody><tr><td align="left" class="navLeft" width="33%"><a accesskey="p" href="parser-gsl.html">Précédent</a></td><td align="center" class="navCenter" width="34%">Répertoire de Fonctions</td><td align="right" class="navRight" width="33%"> <a accesskey="n" href="parser-const.html">Suivant</a></td></tr></tbody></table><div class="sect1"><div class="titlepage"><div><h2 class="title" style="clear: both"><a name="parser-ran-gsl"></a>Distributions de nombres aléatoires de la librairie GSL</h2></div></div><p>Pour plus d'informations au sujet de ces fonctions, veuillez vous référer à la documentation de la librairie GSL. </p><div class="informaltable"><table width="100%" border="1"><colgroup><col><col></colgroup><thead><tr><th>Fonction</th><th>Description</th></tr></thead><tbody><tr><td>gaussian(x,sigma)</td><td>probability density p(x) at X for a Gaussian distribution with standard deviation SIGMA</td></tr><tr><td>ugaussian(x)</td><td>unit Gaussian distribution. They are equivalent to the functions above with a standard deviation of one, SIGMA = 1</td></tr><tr><td>gaussian_tail(x,a,sigma)</td><td>probability density p(x) at X for a Gaussian tail distribution with standard deviation SIGMA and lower limit A</td></tr><tr><td>ugaussian_tail(x,a)</td><td>tail of a unit Gaussian distribution. They are equivalent to the functions above with a standard deviation of one, SIGMA = 1</td></tr><tr><td>bivariate_gaussian(x,y,sigma_x,sigma_y,rho)</td><td>probability density p(x,y) at (X,Y) for a bivariate gaussian distribution with standard deviations SIGMA_X, SIGMA_Y and correlation coefficient RHO</td></tr><tr><td>exponential(x,mu)</td><td>probability density p(x) at X for an exponential distribution with mean MU</td></tr><tr><td>laplace(x,a)</td><td>probability density p(x) at X for a Laplace distribution with mean A</td></tr><tr><td>exppow(x,a,b)</td><td>probability density p(x) at X for an exponential power distribution with scale parameter A and exponent B</td></tr><tr><td>cauchy(x,a)</td><td>probability density p(x) at X for a Cauchy distribution with scale parameter A</td></tr><tr><td>rayleigh(x,sigma)</td><td>probability density p(x) at X for a Rayleigh distribution with scale parameter SIGMA</td></tr><tr><td>rayleigh_tail(x,a,sigma)</td><td>probability density p(x) at X for a Rayleigh tail distribution with scale parameter SIGMA and lower limit A</td></tr><tr><td>landau(x)</td><td>probability density p(x) at X for the Landau distribution</td></tr><tr><td>gamma_pdf(x,a,b)</td><td>probability density p(x) at X for a gamma distribution with parameters A and B</td></tr><tr><td>flat(x,a,b)</td><td>probability density p(x) at X for a uniform distribution from A to B</td></tr><tr><td>lognormal(x,zeta,sigma)</td><td>probability density p(x) at X for a lognormal distribution with parameters ZETA and SIGMA</td></tr><tr><td>chisq(x,nu)</td><td>probability density p(x) at X for a chi-squared distribution with NU degrees of freedom</td></tr><tr><td>fdist(x,nu1,nu2)</td><td>probability density p(x) at X for an F-distribution with NU1 and NU2 degrees of freedom</td></tr><tr><td>tdist(x,nu)</td><td>probability density p(x) at X for a t-distribution with NU degrees of freedom</td></tr><tr><td>beta_pdf(x,a,b)</td><td>probability density p(x) at X for a beta distribution with parameters A and B</td></tr><tr><td>logistic(x,a)</td><td>probability density p(x) at X for a logistic distribution with scale parameter A</td></tr><tr><td>pareto(x,a,b)</td><td>probability density p(x) at X for a Pareto distribution with exponent A and scale B</td></tr><tr><td>weibull(x,a,b)</td><td>probability density p(x) at X for a Weibull distribution with scale A and exponent B</td></tr><tr><td>gumbel1(x,a,b)</td><td>probability density p(x) at X for a Type-1 Gumbel distribution with parameters A and B</td></tr><tr><td>gumbel2(x,a,b)</td><td>probability density p(x) at X for a Type-2 Gumbel distribution with parameters A and B</td></tr><tr><td>poisson(k,mu)</td><td>probability p(k) of obtaining K from a Poisson distribution with mean mu</td></tr><tr><td>bernoulli(k,p)</td><td>probability p(k) of obtaining K from a Bernoulli distribution with probability parameter P</td></tr><tr><td>binomial(k,p,n)</td><td>probability p(k) of obtaining K from a binomial distribution with parameters P and N</td></tr><tr><td>negative_binomial(k,p,n)</td><td>probability p(k) of obtaining K from a negative binomial distribution with parameters P and N</td></tr><tr><td>pascal(k,p,n)</td><td>probability p(k) of obtaining K from a Pascal distribution with parameters P and N</td></tr><tr><td>geometric(k,p)</td><td>probability p(k) of obtaining K from a geometric distribution with probability parameter P</td></tr><tr><td>hypergeometric(k,n1,n2,t)</td><td>probability p(k) of obtaining K from a hypergeometric distribution with parameters N1, N2, N3</td></tr><tr><td>logarithmic(k,p)</td><td>probability p(k) of obtaining K from a logarithmic distribution with probability parameter P</td></tr></tbody></table></div></div><table width="100%" class="bottom-nav"><tr><td width="33%" align="left" valign="top" class="navLeft"><a href="parser-gsl.html">Précédent</a></td><td width="34%" align="center" valign="top" class="navCenter"><a href="index.html">Sommaire</a></td><td width="33%" align="right" valign="top" class="navRight"><a href="parser-const.html">Suivant</a></td></tr><tr><td width="33%" align="left" class="navLeft">Fonctions Spéciales de la librairie GSL </td><td width="34%" align="center" class="navCenter"><a href="parser.html">Niveau supérieur</a></td><td width="33%" align="right" class="navRight"> Constantes</td></tr></table></body></html>
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2010.0
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i586
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993001621d734c58db7369ae7a99e423
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files
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