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492 lines
17 KiB
C++
492 lines
17 KiB
C++
// Copyright John Maddock 2006.
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// Use, modification and distribution are subject to the
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// Boost Software License, Version 1.0. (See accompanying file
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// LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
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// distributions.hpp provides definitions of the concept of a distribution
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// and non-member accessor functions that must be implemented by all distributions.
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// This is used to verify that
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// all the features of a distributions have been fully implemented.
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#ifndef BOOST_MATH_DISTRIBUTION_CONCEPT_HPP
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#define BOOST_MATH_DISTRIBUTION_CONCEPT_HPP
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#include <boost/math/distributions/complement.hpp>
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#include <boost/math/distributions/fwd.hpp>
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#ifdef BOOST_MSVC
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#pragma warning(push)
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#pragma warning(disable: 4100)
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#pragma warning(disable: 4510)
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#pragma warning(disable: 4610)
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#pragma warning(disable: 4189) // local variable is initialized but not referenced.
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#endif
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#include <boost/concept_check.hpp>
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#ifdef BOOST_MSVC
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#pragma warning(pop)
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#endif
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#include <utility>
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namespace boost{
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namespace math{
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namespace concepts
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{
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// Begin by defining a concept archetype
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// for a distribution class:
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//
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template <class RealType>
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class distribution_archetype
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{
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public:
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typedef RealType value_type;
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distribution_archetype(const distribution_archetype&); // Copy constructible.
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distribution_archetype& operator=(const distribution_archetype&); // Assignable.
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// There is no default constructor,
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// but we need a way to instantiate the archetype:
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static distribution_archetype& get_object()
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{
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// will never get caled:
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return *reinterpret_cast<distribution_archetype*>(0);
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}
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}; // template <class RealType>class distribution_archetype
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// Non-member accessor functions:
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// (This list defines the functions that must be implemented by all distributions).
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template <class RealType>
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RealType pdf(const distribution_archetype<RealType>& dist, const RealType& x);
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template <class RealType>
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RealType cdf(const distribution_archetype<RealType>& dist, const RealType& x);
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template <class RealType>
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RealType quantile(const distribution_archetype<RealType>& dist, const RealType& p);
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template <class RealType>
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RealType cdf(const complemented2_type<distribution_archetype<RealType>, RealType>& c);
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template <class RealType>
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RealType quantile(const complemented2_type<distribution_archetype<RealType>, RealType>& c);
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template <class RealType>
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RealType mean(const distribution_archetype<RealType>& dist);
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template <class RealType>
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RealType standard_deviation(const distribution_archetype<RealType>& dist);
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template <class RealType>
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RealType variance(const distribution_archetype<RealType>& dist);
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template <class RealType>
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RealType hazard(const distribution_archetype<RealType>& dist);
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template <class RealType>
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RealType chf(const distribution_archetype<RealType>& dist);
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// http://en.wikipedia.org/wiki/Characteristic_function_%28probability_theory%29
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template <class RealType>
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RealType coefficient_of_variation(const distribution_archetype<RealType>& dist);
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template <class RealType>
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RealType mode(const distribution_archetype<RealType>& dist);
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template <class RealType>
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RealType skewness(const distribution_archetype<RealType>& dist);
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template <class RealType>
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RealType kurtosis_excess(const distribution_archetype<RealType>& dist);
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template <class RealType>
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RealType kurtosis(const distribution_archetype<RealType>& dist);
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template <class RealType>
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RealType median(const distribution_archetype<RealType>& dist);
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template <class RealType>
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std::pair<RealType, RealType> range(const distribution_archetype<RealType>& dist);
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template <class RealType>
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std::pair<RealType, RealType> support(const distribution_archetype<RealType>& dist);
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//
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// Next comes the concept checks for verifying that a class
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// fullfils the requirements of a Distribution:
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//
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template <class Distribution>
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struct DistributionConcept
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{
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typedef typename Distribution::value_type value_type;
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void constraints()
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{
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function_requires<CopyConstructibleConcept<Distribution> >();
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function_requires<AssignableConcept<Distribution> >();
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const Distribution& dist = DistributionConcept<Distribution>::get_object();
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value_type x = 0;
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// The result values are ignored in all these checks.
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value_type v = cdf(dist, x);
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v = cdf(complement(dist, x));
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suppress_unused_variable_warning(v);
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v = pdf(dist, x);
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suppress_unused_variable_warning(v);
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v = quantile(dist, x);
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suppress_unused_variable_warning(v);
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v = quantile(complement(dist, x));
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suppress_unused_variable_warning(v);
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v = mean(dist);
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suppress_unused_variable_warning(v);
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v = mode(dist);
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suppress_unused_variable_warning(v);
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v = standard_deviation(dist);
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suppress_unused_variable_warning(v);
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v = variance(dist);
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suppress_unused_variable_warning(v);
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v = hazard(dist, x);
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suppress_unused_variable_warning(v);
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v = chf(dist, x);
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suppress_unused_variable_warning(v);
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v = coefficient_of_variation(dist);
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suppress_unused_variable_warning(v);
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v = skewness(dist);
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suppress_unused_variable_warning(v);
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v = kurtosis(dist);
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suppress_unused_variable_warning(v);
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v = kurtosis_excess(dist);
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suppress_unused_variable_warning(v);
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v = median(dist);
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suppress_unused_variable_warning(v);
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std::pair<value_type, value_type> pv;
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pv = range(dist);
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suppress_unused_variable_warning(pv);
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pv = support(dist);
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suppress_unused_variable_warning(pv);
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float f = 1;
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v = cdf(dist, f);
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suppress_unused_variable_warning(v);
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v = cdf(complement(dist, f));
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suppress_unused_variable_warning(v);
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v = pdf(dist, f);
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suppress_unused_variable_warning(v);
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v = quantile(dist, f);
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suppress_unused_variable_warning(v);
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v = quantile(complement(dist, f));
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suppress_unused_variable_warning(v);
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v = hazard(dist, f);
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suppress_unused_variable_warning(v);
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v = chf(dist, f);
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suppress_unused_variable_warning(v);
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double d = 1;
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v = cdf(dist, d);
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suppress_unused_variable_warning(v);
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v = cdf(complement(dist, d));
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suppress_unused_variable_warning(v);
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v = pdf(dist, d);
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suppress_unused_variable_warning(v);
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v = quantile(dist, d);
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suppress_unused_variable_warning(v);
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v = quantile(complement(dist, d));
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suppress_unused_variable_warning(v);
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v = hazard(dist, d);
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suppress_unused_variable_warning(v);
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v = chf(dist, d);
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suppress_unused_variable_warning(v);
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#ifndef TEST_MPFR
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long double ld = 1;
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v = cdf(dist, ld);
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suppress_unused_variable_warning(v);
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v = cdf(complement(dist, ld));
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suppress_unused_variable_warning(v);
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v = pdf(dist, ld);
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suppress_unused_variable_warning(v);
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v = quantile(dist, ld);
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suppress_unused_variable_warning(v);
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v = quantile(complement(dist, ld));
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suppress_unused_variable_warning(v);
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v = hazard(dist, ld);
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suppress_unused_variable_warning(v);
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v = chf(dist, ld);
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suppress_unused_variable_warning(v);
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#endif
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int i = 1;
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v = cdf(dist, i);
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suppress_unused_variable_warning(v);
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v = cdf(complement(dist, i));
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suppress_unused_variable_warning(v);
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v = pdf(dist, i);
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suppress_unused_variable_warning(v);
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v = quantile(dist, i);
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suppress_unused_variable_warning(v);
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v = quantile(complement(dist, i));
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suppress_unused_variable_warning(v);
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v = hazard(dist, i);
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suppress_unused_variable_warning(v);
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v = chf(dist, i);
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suppress_unused_variable_warning(v);
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unsigned long li = 1;
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v = cdf(dist, li);
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suppress_unused_variable_warning(v);
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v = cdf(complement(dist, li));
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suppress_unused_variable_warning(v);
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v = pdf(dist, li);
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suppress_unused_variable_warning(v);
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v = quantile(dist, li);
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suppress_unused_variable_warning(v);
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v = quantile(complement(dist, li));
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suppress_unused_variable_warning(v);
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v = hazard(dist, li);
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suppress_unused_variable_warning(v);
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v = chf(dist, li);
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suppress_unused_variable_warning(v);
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test_extra_members(dist);
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}
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template <class D>
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static void test_extra_members(const D&)
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{}
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template <class R, class P>
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static void test_extra_members(const boost::math::bernoulli_distribution<R, P>& d)
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{
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value_type r = d.success_fraction();
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(void)r; // warning suppression
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}
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template <class R, class P>
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static void test_extra_members(const boost::math::beta_distribution<R, P>& d)
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{
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value_type r1 = d.alpha();
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value_type r2 = d.beta();
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r1 = boost::math::beta_distribution<R, P>::find_alpha(r1, r2);
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suppress_unused_variable_warning(r1);
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r1 = boost::math::beta_distribution<R, P>::find_beta(r1, r2);
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suppress_unused_variable_warning(r1);
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r1 = boost::math::beta_distribution<R, P>::find_alpha(r1, r2, r1);
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suppress_unused_variable_warning(r1);
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r1 = boost::math::beta_distribution<R, P>::find_beta(r1, r2, r1);
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suppress_unused_variable_warning(r1);
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}
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template <class R, class P>
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static void test_extra_members(const boost::math::binomial_distribution<R, P>& d)
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{
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value_type r = d.success_fraction();
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r = d.trials();
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r = Distribution::find_lower_bound_on_p(r, r, r);
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r = Distribution::find_lower_bound_on_p(r, r, r, Distribution::clopper_pearson_exact_interval);
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r = Distribution::find_lower_bound_on_p(r, r, r, Distribution::jeffreys_prior_interval);
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r = Distribution::find_upper_bound_on_p(r, r, r);
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r = Distribution::find_upper_bound_on_p(r, r, r, Distribution::clopper_pearson_exact_interval);
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r = Distribution::find_upper_bound_on_p(r, r, r, Distribution::jeffreys_prior_interval);
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r = Distribution::find_minimum_number_of_trials(r, r, r);
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r = Distribution::find_maximum_number_of_trials(r, r, r);
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suppress_unused_variable_warning(r);
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}
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template <class R, class P>
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static void test_extra_members(const boost::math::cauchy_distribution<R, P>& d)
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{
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value_type r = d.location();
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r = d.scale();
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suppress_unused_variable_warning(r);
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}
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template <class R, class P>
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static void test_extra_members(const boost::math::chi_squared_distribution<R, P>& d)
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{
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value_type r = d.degrees_of_freedom();
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r = Distribution::find_degrees_of_freedom(r, r, r, r);
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r = Distribution::find_degrees_of_freedom(r, r, r, r, r);
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suppress_unused_variable_warning(r);
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}
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template <class R, class P>
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static void test_extra_members(const boost::math::exponential_distribution<R, P>& d)
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{
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value_type r = d.lambda();
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suppress_unused_variable_warning(r);
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}
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template <class R, class P>
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static void test_extra_members(const boost::math::extreme_value_distribution<R, P>& d)
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{
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value_type r = d.scale();
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r = d.location();
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suppress_unused_variable_warning(r);
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}
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template <class R, class P>
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static void test_extra_members(const boost::math::fisher_f_distribution<R, P>& d)
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{
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value_type r = d.degrees_of_freedom1();
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r = d.degrees_of_freedom2();
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suppress_unused_variable_warning(r);
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}
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template <class R, class P>
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static void test_extra_members(const boost::math::gamma_distribution<R, P>& d)
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{
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value_type r = d.scale();
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r = d.shape();
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suppress_unused_variable_warning(r);
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}
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template <class R, class P>
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static void test_extra_members(const boost::math::inverse_chi_squared_distribution<R, P>& d)
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{
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value_type r = d.scale();
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r = d.degrees_of_freedom();
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suppress_unused_variable_warning(r);
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}
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template <class R, class P>
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static void test_extra_members(const boost::math::inverse_gamma_distribution<R, P>& d)
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{
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value_type r = d.scale();
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r = d.shape();
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suppress_unused_variable_warning(r);
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}
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template <class R, class P>
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static void test_extra_members(const boost::math::hypergeometric_distribution<R, P>& d)
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{
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unsigned u = d.defective();
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u = d.sample_count();
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u = d.total();
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suppress_unused_variable_warning(u);
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}
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template <class R, class P>
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static void test_extra_members(const boost::math::laplace_distribution<R, P>& d)
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{
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value_type r = d.scale();
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r = d.location();
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suppress_unused_variable_warning(r);
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}
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template <class R, class P>
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static void test_extra_members(const boost::math::logistic_distribution<R, P>& d)
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{
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value_type r = d.scale();
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r = d.location();
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suppress_unused_variable_warning(r);
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}
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template <class R, class P>
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static void test_extra_members(const boost::math::lognormal_distribution<R, P>& d)
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{
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value_type r = d.scale();
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r = d.location();
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suppress_unused_variable_warning(r);
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}
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template <class R, class P>
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static void test_extra_members(const boost::math::negative_binomial_distribution<R, P>& d)
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{
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value_type r = d.success_fraction();
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r = d.successes();
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r = Distribution::find_lower_bound_on_p(r, r, r);
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r = Distribution::find_upper_bound_on_p(r, r, r);
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r = Distribution::find_minimum_number_of_trials(r, r, r);
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r = Distribution::find_maximum_number_of_trials(r, r, r);
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suppress_unused_variable_warning(r);
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}
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template <class R, class P>
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static void test_extra_members(const boost::math::non_central_beta_distribution<R, P>& d)
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{
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value_type r1 = d.alpha();
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value_type r2 = d.beta();
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r1 = d.non_centrality();
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(void)r1; // warning suppression
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(void)r2; // warning suppression
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}
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template <class R, class P>
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static void test_extra_members(const boost::math::non_central_chi_squared_distribution<R, P>& d)
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{
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value_type r = d.degrees_of_freedom();
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r = d.non_centrality();
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r = Distribution::find_degrees_of_freedom(r, r, r);
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r = Distribution::find_degrees_of_freedom(boost::math::complement(r, r, r));
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r = Distribution::find_non_centrality(r, r, r);
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r = Distribution::find_non_centrality(boost::math::complement(r, r, r));
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(void)r; // warning suppression
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}
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template <class R, class P>
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static void test_extra_members(const boost::math::non_central_f_distribution<R, P>& d)
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{
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value_type r = d.degrees_of_freedom1();
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r = d.degrees_of_freedom2();
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r = d.non_centrality();
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(void)r; // warning suppression
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}
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template <class R, class P>
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static void test_extra_members(const boost::math::non_central_t_distribution<R, P>& d)
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{
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value_type r = d.degrees_of_freedom();
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r = d.non_centrality();
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(void)r; // warning suppression
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}
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template <class R, class P>
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static void test_extra_members(const boost::math::normal_distribution<R, P>& d)
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{
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value_type r = d.scale();
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r = d.location();
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r = d.mean();
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r = d.standard_deviation();
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(void)r; // warning suppression
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}
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template <class R, class P>
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static void test_extra_members(const boost::math::pareto_distribution<R, P>& d)
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{
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value_type r = d.scale();
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r = d.shape();
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(void)r; // warning suppression
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}
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template <class R, class P>
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static void test_extra_members(const boost::math::poisson_distribution<R, P>& d)
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{
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value_type r = d.mean();
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(void)r; // warning suppression
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}
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template <class R, class P>
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static void test_extra_members(const boost::math::rayleigh_distribution<R, P>& d)
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{
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value_type r = d.sigma();
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(void)r; // warning suppression
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}
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template <class R, class P>
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static void test_extra_members(const boost::math::students_t_distribution<R, P>& d)
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{
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value_type r = d.degrees_of_freedom();
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r = d.find_degrees_of_freedom(r, r, r, r);
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r = d.find_degrees_of_freedom(r, r, r, r, r);
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(void)r; // warning suppression
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}
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template <class R, class P>
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static void test_extra_members(const boost::math::triangular_distribution<R, P>& d)
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{
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value_type r = d.lower();
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r = d.mode();
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r = d.upper();
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(void)r; // warning suppression
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}
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template <class R, class P>
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static void test_extra_members(const boost::math::weibull_distribution<R, P>& d)
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|
{
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|
value_type r = d.scale();
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|
r = d.shape();
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|
(void)r; // warning suppression
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|
}
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|
template <class R, class P>
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|
static void test_extra_members(const boost::math::uniform_distribution<R, P>& d)
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|
{
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|
value_type r = d.lower();
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|
r = d.upper();
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|
(void)r; // warning suppression
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|
}
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|
private:
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|
static Distribution* pd;
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|
static Distribution& get_object()
|
|
{
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|
// In reality this will never get called:
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|
return *pd;
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|
}
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|
}; // struct DistributionConcept
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|
|
|
template <class Distribution>
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|
Distribution* DistributionConcept<Distribution>::pd = 0;
|
|
|
|
} // namespace concepts
|
|
} // namespace math
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|
} // namespace boost
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|
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|
#endif // BOOST_MATH_DISTRIBUTION_CONCEPT_HPP
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|
|