/usr/include/ql/experimental/math/claytoncopularng.hpp is in libquantlib0-dev 1.7.1-1.
This file is owned by root:root, with mode 0o644.
The actual contents of the file can be viewed below.
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/*
Copyright (C) 2010 Hachemi Benyahia
Copyright (C) 2010 DeriveXperts SAS
This file is part of QuantLib, a free-software/open-source library
for financial quantitative analysts and developers - http://quantlib.org/
QuantLib is free software: you can redistribute it and/or modify it
under the terms of the QuantLib license. You should have received a
copy of the license along with this program; if not, please email
<quantlib-dev@lists.sf.net>. The license is also available online at
<http://quantlib.org/license.shtml>.
This program is distributed in the hope that it will be useful, but WITHOUT
ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
FOR A PARTICULAR PURPOSE. See the license for more details.
*/
/*! \file claytoncopularng.hpp
\brief Clayton copula random-number generator
*/
#ifndef quantlib_clayton_copula_rng_hpp
#define quantlib_clayton_copula_rng_hpp
#include <ql/methods/montecarlo/sample.hpp>
#include <ql/errors.hpp>
#include <vector>
namespace QuantLib {
//! Clayton copula random-number generator
template <class RNG>
class ClaytonCopulaRng {
public:
typedef Sample<std::vector<Real> > sample_type;
typedef RNG urng_type;
explicit ClaytonCopulaRng(const RNG& uniformGenerator,Real theta);
sample_type next() const;
private:
Real theta_;
RNG uniformGenerator_;
};
template <class RNG>
ClaytonCopulaRng<RNG>::ClaytonCopulaRng(const RNG& ug, Real th)
: uniformGenerator_(ug), theta_(th) {
QL_REQUIRE(th >= -1.0,
"theta (" << th << ") must be greater or equal to -1");
QL_REQUIRE(th != 0.0,
"theta (" << th << ") must be different from 0");
}
template <class RNG>
inline typename ClaytonCopulaRng<RNG>::sample_type
ClaytonCopulaRng<RNG>::next() const {
typename RNG::sample_type v1 = uniformGenerator_.next();
typename RNG::sample_type v2 = uniformGenerator_.next();
Real u1 = v1.value;
Real u2 = std::pow(std::pow(v1.value,-theta_)*(std::pow(v2.value,-theta_/(theta_+1.0))-1.0)+1.0,-1.0/theta_);
std::vector<Real> u;
u.push_back(u1);
u.push_back(u2);
return sample_type(u,v1.weight*v2.weight);
}
}
#endif
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