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## root / tmp / org.txm.statsengine.r.core.win32 / res / win32 / library / BH / include / boost / accumulators / statistics / weighted_covariance.hpp @ 2486

 1 ///////////////////////////////////////////////////////////////////////////////  // weighted_covariance.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_COVARIANCE_HPP_DE_01_01_2006  #define BOOST_ACCUMULATORS_STATISTICS_WEIGHTED_COVARIANCE_HPP_DE_01_01_2006  #include  #include  #include  #include  #include  #include  #include  #include  #include  #include  #include  #include  #include  #include  #include  #include  #include  #include  #include  #include  #include // for numeric::outer_product() and type traits  #include  namespace boost { namespace accumulators  {  namespace impl  {   ///////////////////////////////////////////////////////////////////////////////   // weighted_covariance_impl   //   /**   @brief Weighted Covariance Estimator     An iterative Monte Carlo estimator for the weighted covariance \f$\mathrm{Cov}(X,X')\f$, where \f$X\f$ is a sample   and \f$X'\f$ a variate, is given by:     \f[   \hat{c}_n = \frac{\bar{w}_n-w_n}{\bar{w}_n} \hat{c}_{n-1} + \frac{w_n}{\bar{w}_n-w_n}(X_n - \hat{\mu}_n)(X_n' - \hat{\mu}_n'),   \quad n\ge2,\quad\hat{c}_1 = 0,   \f]     \f$\hat{\mu}_n\f$ and \f$\hat{\mu}_n'\f$ being the weighted means of the samples and variates and   \f$\bar{w}_n\f$ the sum of the \f$n\f$ first weights \f$w_i\f$.   */   template   struct weighted_covariance_impl   : accumulator_base   {   typedef typename numeric::functional::multiplies::result_type>::result_type weighted_sample_type;   typedef typename numeric::functional::multiplies::result_type>::result_type weighted_variate_type;   // for boost::result_of   typedef typename numeric::functional::outer_product::result_type result_type;   template   weighted_covariance_impl(Args const &args)   : cov_(   numeric::outer_product(   numeric::fdiv(args[sample | Sample()], (std::size_t)1)   * numeric::one::value   , numeric::fdiv(args[parameter::keyword::get() | VariateType()], (std::size_t)1)   * numeric::one::value   )   )   {   }   template   void operator ()(Args const &args)   {   std::size_t cnt = count(args);   if (cnt > 1)   {   extractor > const some_weighted_mean_of_variates = {};   this->cov_ = this->cov_ * (sum_of_weights(args) - args[weight]) / sum_of_weights(args)   + numeric::outer_product(   some_weighted_mean_of_variates(args) - args[parameter::keyword::get()]   , weighted_mean(args) - args[sample]   ) * args[weight] / (sum_of_weights(args) - args[weight]);   }   }   result_type result(dont_care) const   {   return this->cov_;   }   private:   result_type cov_;   };  } // namespace impl  ///////////////////////////////////////////////////////////////////////////////  // tag::weighted_covariance  //  namespace tag  {   template   struct weighted_covariance   : depends_on >   {   typedef accumulators::impl::weighted_covariance_impl impl;   };  }  ///////////////////////////////////////////////////////////////////////////////  // extract::weighted_covariance  //  namespace extract  {   extractor const weighted_covariance = {};   BOOST_ACCUMULATORS_IGNORE_GLOBAL(weighted_covariance)  }  using extract::weighted_covariance;  }} // namespace boost::accumulators  #endif