/////////////////////////////////////////////////////////////////////////////// // weighted_tail_quantile.hpp // // Copyright 2006 Daniel Egloff, Olivier Gygi. 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) #ifndef BOOST_ACCUMULATORS_STATISTICS_WEIGHTED_TAIL_QUANTILE_HPP_DE_01_01_2006 #define BOOST_ACCUMULATORS_STATISTICS_WEIGHTED_TAIL_QUANTILE_HPP_DE_01_01_2006 #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #ifdef _MSC_VER # pragma warning(push) # pragma warning(disable: 4127) // conditional expression is constant #endif namespace boost { namespace accumulators { namespace impl { /////////////////////////////////////////////////////////////////////////////// // weighted_tail_quantile_impl // Tail quantile estimation based on order statistics of weighted samples /** @brief Tail quantile estimation based on order statistics of weighted samples (for both left and right tails) An estimator \f$\hat{q}\f$ of tail quantiles with level \f$\alpha\f$ based on order statistics \f$X_{1:n} \leq X_{2:n} \leq\dots\leq X_{n:n}\f$ of weighted samples are given by \f$X_{\lambda:n}\f$ (left tail) and \f$X_{\rho:n}\f$ (right tail), where \f[ \lambda = \inf\left\{ l \left| \frac{1}{\bar{w}_n}\sum_{i=1}^{l} w_i \geq \alpha \right. \right\} \f] and \f[ \rho = \sup\left\{ r \left| \frac{1}{\bar{w}_n}\sum_{i=r}^{n} w_i \geq (1 - \alpha) \right. \right\}, \f] \f$n\f$ being the number of samples and \f$\bar{w}_n\f$ the sum of all weights. @param quantile_probability */ template struct weighted_tail_quantile_impl : accumulator_base { typedef typename numeric::functional::fdiv::result_type float_type; // for boost::result_of typedef Sample result_type; weighted_tail_quantile_impl(dont_care) {} template result_type result(Args const &args) const { float_type threshold = sum_of_weights(args) * ( ( is_same::value ) ? args[quantile_probability] : 1. - args[quantile_probability] ); std::size_t n = 0; Weight sum = Weight(0); while (sum < threshold) { if (n < static_cast(tail_weights(args).size())) { sum += *(tail_weights(args).begin() + n); n++; } else { if (std::numeric_limits::has_quiet_NaN) { return std::numeric_limits::quiet_NaN(); } else { std::ostringstream msg; msg << "index n = " << n << " is not in valid range [0, " << tail(args).size() << ")"; boost::throw_exception(std::runtime_error(msg.str())); return Sample(0); } } } // Note that the cached samples of the left are sorted in ascending order, // whereas the samples of the right tail are sorted in descending order return *(boost::begin(tail(args)) + n - 1); } }; } // namespace impl /////////////////////////////////////////////////////////////////////////////// // tag::weighted_tail_quantile<> // namespace tag { template struct weighted_tail_quantile : depends_on > { /// INTERNAL ONLY typedef accumulators::impl::weighted_tail_quantile_impl impl; }; } /////////////////////////////////////////////////////////////////////////////// // extract::weighted_tail_quantile // namespace extract { extractor const weighted_tail_quantile = {}; BOOST_ACCUMULATORS_IGNORE_GLOBAL(weighted_tail_quantile) } using extract::weighted_tail_quantile; }} // namespace boost::accumulators #ifdef _MSC_VER # pragma warning(pop) #endif #endif