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		<summary type="html">&lt;p&gt;193.136.196.12: /* Nature of the one-way function */&lt;/p&gt;
&lt;hr /&gt;
&lt;div&gt;The term &#039;&#039;&#039;generalized logistic distribution&#039;&#039;&#039; is used as the name for several different families of [[probability distributions]]. For example, Johnson et al.&amp;lt;ref name=J1&amp;gt;Johnson, N.L., Kotz, S., Balakrishnan, N. (1995) &#039;&#039;Continuous Univariate Distributions, Volume 2&#039;&#039;, Wiley. ISBN 0-471-58494-0 (pages 140–142)&amp;lt;/ref&amp;gt; list four forms, which are listed below. One family described here has also been called the &#039;&#039;&#039;skew-logistic distribution&#039;&#039;&#039;. For other families of distributions that have also been called generalized logistic distributions, see the [[Log-logistic distribution#Shifted log-logistic distribution|shifted log-logistic distribution]], which is a generalization of the [[log-logistic distribution]].&lt;br /&gt;
&lt;br /&gt;
==Definitions==&lt;br /&gt;
&lt;br /&gt;
The following definitions are for standardized versions of the families, which can be expanded to the full form as a [[location-scale family]]. Each is defined using either the [[cumulative distribution function]] (&#039;&#039;F&#039;&#039;) or the [[probability density function]] (&#039;&#039;&amp;amp;fnof;&#039;&#039;), and is defined on (-∞,∞).&lt;br /&gt;
&lt;br /&gt;
===Type I===&lt;br /&gt;
:&amp;lt;math&amp;gt;F(x;\alpha)=\frac{1}{(1+\exp(-x))^\alpha} \equiv (1+\exp(-x))^{-\alpha}, \quad \alpha &amp;gt; 0 .&amp;lt;/math&amp;gt;&lt;br /&gt;
The corresponding probability density function is:&lt;br /&gt;
:&amp;lt;math&amp;gt;f(x;\alpha)=\frac{\alpha \exp(-x)}{\left(1+\exp(-x)\right)^{\alpha+1}}, \quad \alpha &amp;gt; 0 .&amp;lt;/math&amp;gt;&lt;br /&gt;
This type has also been called the &amp;quot;skew-logistic&amp;quot; distribution.&lt;br /&gt;
&lt;br /&gt;
===Type II ===&lt;br /&gt;
:&amp;lt;math&amp;gt;F(x;\alpha)=1-\frac{\exp(-\alpha x)}{(1+\exp(-x))^\alpha}, \quad \alpha &amp;gt; 0 .&amp;lt;/math&amp;gt;&lt;br /&gt;
&lt;br /&gt;
===Type III ===&lt;br /&gt;
:&amp;lt;math&amp;gt;f(x;\alpha)=\frac{1}{B(\alpha,\alpha)}\frac{\exp(-\alpha x)}{(1+\exp(-x))^{2\alpha}}, \quad \alpha &amp;gt; 0 .&amp;lt;/math&amp;gt;&lt;br /&gt;
Here &#039;&#039;B&#039;&#039; is the [[beta function]]. The [[moment generating function]] for this type is&lt;br /&gt;
:&amp;lt;math&amp;gt;M(t)=\frac{\Gamma(\alpha-t) \Gamma(\alpha+t) }{ (\Gamma(\alpha))^2 }, \quad -\alpha&amp;lt;t&amp;lt;\alpha.&amp;lt;/math&amp;gt; &lt;br /&gt;
&lt;br /&gt;
===Type IV ===&lt;br /&gt;
:&amp;lt;math&amp;gt;f(x;\alpha,\beta)=\frac{1}{B(\alpha,\beta)}\frac{\exp(-\beta x)}{(1+\exp(-x))^{\alpha+\beta}}, \quad \alpha,\beta &amp;gt; 0 .&amp;lt;/math&amp;gt;&lt;br /&gt;
Again, &#039;&#039;B&#039;&#039; is the [[beta function]]. The [[moment generating function]] for this type is&lt;br /&gt;
:&amp;lt;math&amp;gt;M(t)=\frac{\Gamma(\beta-t) \Gamma(\alpha+t) }{ \Gamma(\alpha) \Gamma(\beta) }, \quad -\alpha&amp;lt;t&amp;lt;\beta.&amp;lt;/math&amp;gt; &lt;br /&gt;
This type is also called the &amp;quot;exponential generalized beta of the second type&amp;quot;.&amp;lt;ref name=J1/&amp;gt;&lt;br /&gt;
&lt;br /&gt;
==See also==&lt;br /&gt;
*[[Champernowne distribution]], another generalization of the logistic distribution.&lt;br /&gt;
&lt;br /&gt;
==References==&lt;br /&gt;
&amp;lt;references/&amp;gt;&lt;br /&gt;
&lt;br /&gt;
{{ProbDistributions|continuous-infinite}}&lt;br /&gt;
&lt;br /&gt;
[[Category:Continuous distributions]]&lt;br /&gt;
[[Category:Probability distributions]]&lt;br /&gt;
{{statistics-stub}}&lt;/div&gt;</summary>
		<author><name>193.136.196.12</name></author>
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