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///////////////////////////////////////////////////////////////////////////////
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// weighted_tail_mean.hpp
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//
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//  Copyright 2006 Daniel Egloff, Olivier Gygi. Distributed under the Boost
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//  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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#ifndef BOOST_ACCUMULATORS_STATISTICS_WEIGHTED_TAIL_MEAN_HPP_DE_01_01_2006
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#define BOOST_ACCUMULATORS_STATISTICS_WEIGHTED_TAIL_MEAN_HPP_DE_01_01_2006
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#include <numeric>
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#include <vector>
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#include <limits>
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#include <functional>
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#include <sstream>
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#include <stdexcept>
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#include <boost/throw_exception.hpp>
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#include <boost/parameter/keyword.hpp>
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#include <boost/mpl/placeholders.hpp>
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#include <boost/type_traits/is_same.hpp>
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#include <boost/accumulators/numeric/functional.hpp>
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#include <boost/accumulators/framework/accumulator_base.hpp>
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#include <boost/accumulators/framework/extractor.hpp>
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#include <boost/accumulators/framework/parameters/sample.hpp>
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#include <boost/accumulators/statistics_fwd.hpp>
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#include <boost/accumulators/statistics/tail.hpp>
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#include <boost/accumulators/statistics/tail_mean.hpp>
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#include <boost/accumulators/statistics/parameters/quantile_probability.hpp>
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#ifdef _MSC_VER
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# pragma warning(push)
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# pragma warning(disable: 4127) // conditional expression is constant
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#endif
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namespace boost { namespace accumulators
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{
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namespace impl
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{
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    ///////////////////////////////////////////////////////////////////////////////
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    // coherent_weighted_tail_mean_impl
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    //
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    // TODO
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    ///////////////////////////////////////////////////////////////////////////////
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    // non_coherent_weighted_tail_mean_impl
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    //
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    /**
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        @brief Estimation of the (non-coherent) weighted tail mean based on order statistics (for both left and right tails)
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        An estimation of the non-coherent, weighted tail mean \f$\widehat{NCTM}_{n,\alpha}(X)\f$ is given by the weighted mean
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        of the
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        \f[
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            \lambda = \inf\left\{ l \left| \frac{1}{\bar{w}_n}\sum_{i=1}^{l} w_i \geq \alpha \right. \right\}
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        \f]
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        smallest samples (left tail) or the weighted mean of the
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        \f[
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            n + 1 - \rho = n + 1 - \sup\left\{ r \left| \frac{1}{\bar{w}_n}\sum_{i=r}^{n} w_i \geq (1 - \alpha) \right. \right\}
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        \f]
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        largest samples (right tail) above a quantile \f$\hat{q}_{\alpha}\f$ of level \f$\alpha\f$, \f$n\f$ being the total number of sample
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        and \f$\bar{w}_n\f$ the sum of all \f$n\f$ weights:
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        \f[
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            \widehat{NCTM}_{n,\alpha}^{\mathrm{left}}(X) = \frac{\sum_{i=1}^{\lambda} w_i X_{i:n}}{\sum_{i=1}^{\lambda} w_i},
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        \f]
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        \f[
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            \widehat{NCTM}_{n,\alpha}^{\mathrm{right}}(X) = \frac{\sum_{i=\rho}^n w_i X_{i:n}}{\sum_{i=\rho}^n w_i}.
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        \f]
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        @param quantile_probability
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    */
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    template<typename Sample, typename Weight, typename LeftRight>
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    struct non_coherent_weighted_tail_mean_impl
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      : accumulator_base
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    {
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        typedef typename numeric::functional::multiplies<Sample, Weight>::result_type weighted_sample;
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        typedef typename numeric::functional::fdiv<Weight, std::size_t>::result_type float_type;
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        // for boost::result_of
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        typedef typename numeric::functional::fdiv<weighted_sample, std::size_t>::result_type result_type;
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        non_coherent_weighted_tail_mean_impl(dont_care) {}
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        template<typename Args>
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        result_type result(Args const &args) const
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        {
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            float_type threshold = sum_of_weights(args)
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                             * ( ( is_same<LeftRight, left>::value ) ? args[quantile_probability] : 1. - args[quantile_probability] );
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            std::size_t n = 0;
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            Weight sum = Weight(0);
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            while (sum < threshold)
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            {
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                if (n < static_cast<std::size_t>(tail_weights(args).size()))
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                {
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                    sum += *(tail_weights(args).begin() + n);
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                    n++;
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                }
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                else
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                {
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                    if (std::numeric_limits<result_type>::has_quiet_NaN)
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                    {
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                        return std::numeric_limits<result_type>::quiet_NaN();
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                    }
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                    else
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                    {
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                        std::ostringstream msg;
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                        msg << "index n = " << n << " is not in valid range [0, " << tail(args).size() << ")";
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                        boost::throw_exception(std::runtime_error(msg.str()));
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                        return result_type(0);
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                    }
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                }
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            }
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            return numeric::fdiv(
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                std::inner_product(
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                    tail(args).begin()
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                  , tail(args).begin() + n
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                  , tail_weights(args).begin()
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                  , weighted_sample(0)
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                )
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              , sum
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            );
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        }
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    };
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} // namespace impl
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///////////////////////////////////////////////////////////////////////////////
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// tag::non_coherent_weighted_tail_mean<>
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//
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namespace tag
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{
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    template<typename LeftRight>
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    struct non_coherent_weighted_tail_mean
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      : depends_on<sum_of_weights, tail_weights<LeftRight> >
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    {
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        typedef accumulators::impl::non_coherent_weighted_tail_mean_impl<mpl::_1, mpl::_2, LeftRight> impl;
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    };
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}
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///////////////////////////////////////////////////////////////////////////////
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// extract::non_coherent_weighted_tail_mean;
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//
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namespace extract
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{
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    extractor<tag::abstract_non_coherent_tail_mean> const non_coherent_weighted_tail_mean = {};
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    BOOST_ACCUMULATORS_IGNORE_GLOBAL(non_coherent_weighted_tail_mean)
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}
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using extract::non_coherent_weighted_tail_mean;
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}} // namespace boost::accumulators
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#ifdef _MSC_VER
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# pragma warning(pop)
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#endif
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#endif