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+///////////////////////////////////////////////////////////////////////////////
+// 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 <vector>
+#include <limits>
+#include <numeric>
+#include <functional>
+#include <complex>
+#include <boost/mpl/assert.hpp>
+#include <boost/mpl/bool.hpp>
+#include <boost/range.hpp>
+#include <boost/parameter/keyword.hpp>
+#include <boost/mpl/placeholders.hpp>
+#include <boost/numeric/ublas/io.hpp>
+#include <boost/numeric/ublas/matrix.hpp>
+#include <boost/type_traits/is_scalar.hpp>
+#include <boost/type_traits/is_same.hpp>
+#include <boost/accumulators/framework/accumulator_base.hpp>
+#include <boost/accumulators/framework/extractor.hpp>
+#include <boost/accumulators/numeric/functional.hpp>
+#include <boost/accumulators/framework/parameters/sample.hpp>
+#include <boost/accumulators/statistics_fwd.hpp>
+#include <boost/accumulators/statistics/count.hpp>
+#include <boost/accumulators/statistics/covariance.hpp> // for numeric::outer_product() and type traits
+#include <boost/accumulators/statistics/weighted_mean.hpp>
+
+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<typename Sample, typename Weight, typename VariateType, typename VariateTag>
+    struct weighted_covariance_impl
+      : accumulator_base
+    {
+        typedef typename numeric::functional::multiplies<Weight, typename numeric::functional::average<Sample, std::size_t>::result_type>::result_type weighted_sample_type;
+        typedef typename numeric::functional::multiplies<Weight, typename numeric::functional::average<VariateType, std::size_t>::result_type>::result_type weighted_variate_type;
+        // for boost::result_of
+        typedef typename numeric::functional::outer_product<weighted_sample_type, weighted_variate_type>::result_type result_type;
+
+        template<typename Args>
+        weighted_covariance_impl(Args const &args)
+          : cov_(
+                numeric::outer_product(
+                    numeric::average(args[sample | Sample()], (std::size_t)1)
+                      * numeric::one<Weight>::value
+                  , numeric::average(args[parameter::keyword<VariateTag>::get() | VariateType()], (std::size_t)1)
+                      * numeric::one<Weight>::value
+                )
+            )
+        {
+        }
+
+        template<typename Args>
+        void operator ()(Args const &args)
+        {
+            std::size_t cnt = count(args);
+
+            if (cnt > 1)
+            {
+                extractor<tag::weighted_mean_of_variates<VariateType, VariateTag> > 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<VariateTag>::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<typename VariateType, typename VariateTag>
+    struct weighted_covariance
+      : depends_on<count, sum_of_weights, weighted_mean, weighted_mean_of_variates<VariateType, VariateTag> >
+    {
+        typedef accumulators::impl::weighted_covariance_impl<mpl::_1, mpl::_2, VariateType, VariateTag> impl;
+    };
+}
+
+///////////////////////////////////////////////////////////////////////////////
+// extract::weighted_covariance
+//
+namespace extract
+{
+    extractor<tag::abstract_covariance> const weighted_covariance = {};
+
+    BOOST_ACCUMULATORS_IGNORE_GLOBAL(weighted_covariance)
+}
+
+using extract::weighted_covariance;
+
+}} // namespace boost::accumulators
+
+#endif