frankcopularng.hpp

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/* -*- mode: c++; tab-width: 4; indent-tabs-mode: nil; c-basic-offset: 4 -*- */
 
/*
 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 frankcopularng.hpp
    \brief Frank copula random-number generator
*/
 
#ifndef quantlib_frank_copula_rng_hpp
#define quantlib_frank_copula_rng_hpp
 
#include <ql/methods/montecarlo/sample.hpp>
#include <ql/errors.hpp>
#include <vector>
 
namespace QuantLib {
 
    //! Frank copula random-number generator
    template <class RNG>
    class FrankCopulaRng {
      public:
        typedef Sample<std::vector<Real> > sample_type;
        typedef RNG urng_type;
        explicit FrankCopulaRng(const RNG& uniformGenerator, Real theta);
        sample_type next() const;
      private:
        Real theta_;
        RNG uniformGenerator_;
    };
 
    template <class RNG>
    FrankCopulaRng<RNG>::FrankCopulaRng(const RNG& ug, Real th)
    : uniformGenerator_(ug), theta_(th) {
     QL_REQUIRE(th != 0.0,
                   "theta (" << th << ") must be different from 0");
    }
 
    template <class RNG>
    inline typename FrankCopulaRng<RNG>::sample_type
    FrankCopulaRng<RNG>::next() const {
        typename RNG::sample_type v1 = uniformGenerator_.next();
        typename RNG::sample_type v2 = uniformGenerator_.next();
        Real u1 = v1.value;
        Real u2 = (-1.0/theta_)*std::log(1.0+(v2.value*(1.0-std::exp(-theta_)))/(v2.value*(std::exp(-theta_*v1.value)-1.0)-std::exp(-theta_*v1.value)));
        std::vector<Real> u;
        u.push_back(u1);
        u.push_back(u2);
        return sample_type(u,v1.weight*v2.weight);
    }
 
}
 
 
#endif