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[section:extreme_dist Extreme Value Distribution]
``#include <boost/math/distributions/extreme.hpp>``
template <class RealType = double,
class ``__Policy`` = ``__policy_class`` >
class extreme_value_distribution;
typedef extreme_value_distribution<> extreme_value;
template <class RealType, class ``__Policy``>
class extreme_value_distribution
{
public:
typedef RealType value_type;
extreme_value_distribution(RealType location = 0, RealType scale = 1);
RealType scale()const;
RealType location()const;
};
There are various
[@http://mathworld.wolfram.com/ExtremeValueDistribution.html extreme value distributions]
: this implementation represents the maximum case,
and is variously known as a Fisher-Tippett distribution,
a log-Weibull distribution or a Gumbel distribution.
Extreme value theory is important for assessing risk for highly unusual events,
such as 100-year floods.
More information can be found on the
[@http://www.itl.nist.gov/div898/handbook/eda/section3/eda366g.htm NIST],
[@http://en.wikipedia.org/wiki/Extreme_value_distribution Wikipedia],
[@http://mathworld.wolfram.com/ExtremeValueDistribution.html Mathworld],
and [@http://en.wikipedia.org/wiki/Extreme_value_theory Extreme value theory]
websites.
The relationship of the types of extreme value distributions, of which this is but one, is
discussed by
[@http://www.worldscibooks.com/mathematics/p191.html Extreme Value Distributions, Theory and Applications
Samuel Kotz & Saralees Nadarajah].
The distribution has a PDF given by:
f(x) = (1/scale) e[super -(x-location)/scale] e[super -e[super -(x-location)/scale]]
Which in the standard case (scale = 1, location = 0) reduces to:
f(x) = e[super -x]e[super -e[super -x]]
The following graph illustrates how the PDF varies with the location parameter:
[graph extreme_value_pdf1]
And this graph illustrates how the PDF varies with the shape parameter:
[graph extreme_value_pdf2]
[h4 Member Functions]
extreme_value_distribution(RealType location = 0, RealType scale = 1);
Constructs an Extreme Value distribution with the specified location and scale
parameters.
Requires `scale > 0`, otherwise calls __domain_error.
RealType location()const;
Returns the location parameter of the distribution.
RealType scale()const;
Returns the scale parameter of the distribution.
[h4 Non-member Accessors]
All the [link math_toolkit.dist.dist_ref.nmp usual non-member accessor functions]
that are generic to all distributions are supported: __usual_accessors.
The domain of the random parameter is \[-[infin], +[infin]\].
[h4 Accuracy]
The extreme value distribution is implemented in terms of the
standard library `exp` and `log` functions and as such should have very low
error rates.
[h4 Implementation]
In the following table:
/a/ is the location parameter, /b/ is the scale parameter,
/x/ is the random variate, /p/ is the probability and /q = 1-p/.
[table
[[Function][Implementation Notes]]
[[pdf][Using the relation: pdf = exp((a-x)/b) * exp(-exp((a-x)/b)) / b ]]
[[cdf][Using the relation: p = exp(-exp((a-x)/b)) ]]
[[cdf complement][Using the relation: q = -expm1(-exp((a-x)/b)) ]]
[[quantile][Using the relation: a - log(-log(p)) * b]]
[[quantile from the complement][Using the relation: a - log(-log1p(-q)) * b]]
[[mean][a + [@http://en.wikipedia.org/wiki/Euler-Mascheroni_constant Euler-Mascheroni-constant] * b]]
[[standard deviation][pi * b / sqrt(6)]]
[[mode][The same as the location parameter /a/.]]
[[skewness][12 * sqrt(6) * zeta(3) / pi[super 3] ]]
[[kurtosis][27 / 5]]
[[kurtosis excess][kurtosis - 3 or 12 / 5]]
]
[endsect][/section:extreme_dist Extreme Value]
[/ extreme_value.qbk
Copyright 2006 John Maddock and Paul A. Bristow.
Distributed under the Boost Software License, Version 1.0.
(See accompanying file LICENSE_1_0.txt or copy at
http://www.boost.org/LICENSE_1_0.txt).
]
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