Blurb::
Aleatory uncertain variable - Frechet
Description::
The Frechet distribution is also referred to as the Type II Largest Extreme Value distribution. 
The distribution of maxima in sample sets from a population with a lognormal distribution will asymptotically converge to this distribution. It is commonly used to model non-negative demand variables.

The density function for the frechet distribution is: 
\f[f(x) = \frac{\alpha}{\beta}
	  \left( \frac{\beta}{x} \right)^{\alpha+1}
	  \exp \left( -\left(\frac{\beta}{x}\right)^\alpha \right),
\f]
\f$\mu = \beta\Gamma(1-\frac{1}{\alpha}),\f$ and 
\f$\sigma^2 = \beta^2[\Gamma(1-\frac{2}{\alpha})-\Gamma^2(1-\frac{1}{\alpha})]\f$

Topics::	continuous_variables, aleatory_uncertain_variables
Examples::
Theory::
When used with some methods such as design of experiments and
multidimensional parameter studies, distribution bounds are inferred
to be [0, \f$\mu + 3 \sigma\f$].

For some methods, including vector and centered parameter studies, an
initial point is needed for the uncertain variables. When not given
explicitly, these variables are initialized to their means.

Faq::
See_Also::	
