123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960616263646566676869707172737475767778798081828384858687888990919293949596979899100101102103104105 |
- ///////////////////////////////////////////////////////////////////////////////
- // weighted_kurtosis.hpp
- //
- // Copyright 2006 Olivier Gygi, Daniel Egloff. 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_KURTOSIS_HPP_EAN_28_10_2005
- #define BOOST_ACCUMULATORS_STATISTICS_WEIGHTED_KURTOSIS_HPP_EAN_28_10_2005
- #include <limits>
- #include <boost/mpl/placeholders.hpp>
- #include <boost/accumulators/framework/accumulator_base.hpp>
- #include <boost/accumulators/framework/extractor.hpp>
- #include <boost/accumulators/framework/parameters/sample.hpp>
- #include <boost/accumulators/numeric/functional.hpp>
- #include <boost/accumulators/framework/depends_on.hpp>
- #include <boost/accumulators/statistics_fwd.hpp>
- #include <boost/accumulators/statistics/weighted_moment.hpp>
- #include <boost/accumulators/statistics/weighted_mean.hpp>
- namespace boost { namespace accumulators
- {
- namespace impl
- {
- ///////////////////////////////////////////////////////////////////////////////
- // weighted_kurtosis_impl
- /**
- @brief Kurtosis estimation for weighted samples
- The kurtosis of a sample distribution is defined as the ratio of the 4th central moment and the square of the 2nd central
- moment (the variance) of the samples, minus 3. The term \f$ -3 \f$ is added in order to ensure that the normal distribution
- has zero kurtosis. The kurtosis can also be expressed by the simple moments:
- \f[
- \hat{g}_2 =
- \frac
- {\widehat{m}_n^{(4)}-4\widehat{m}_n^{(3)}\hat{\mu}_n+6\widehat{m}_n^{(2)}\hat{\mu}_n^2-3\hat{\mu}_n^4}
- {\left(\widehat{m}_n^{(2)} - \hat{\mu}_n^{2}\right)^2} - 3,
- \f]
- where \f$ \widehat{m}_n^{(i)} \f$ are the \f$ i \f$-th moment and \f$ \hat{\mu}_n \f$ the mean (first moment) of the
- \f$ n \f$ samples.
- The kurtosis estimator for weighted samples is formally identical to the estimator for unweighted samples, except that
- the weighted counterparts of all measures it depends on are to be taken.
- */
- template<typename Sample, typename Weight>
- struct weighted_kurtosis_impl
- : accumulator_base
- {
- typedef typename numeric::functional::multiplies<Sample, Weight>::result_type weighted_sample;
- // for boost::result_of
- typedef typename numeric::functional::fdiv<weighted_sample, weighted_sample>::result_type result_type;
- weighted_kurtosis_impl(dont_care)
- {
- }
- template<typename Args>
- result_type result(Args const &args) const
- {
- return numeric::fdiv(
- accumulators::weighted_moment<4>(args)
- - 4. * accumulators::weighted_moment<3>(args) * weighted_mean(args)
- + 6. * accumulators::weighted_moment<2>(args) * weighted_mean(args) * weighted_mean(args)
- - 3. * weighted_mean(args) * weighted_mean(args) * weighted_mean(args) * weighted_mean(args)
- , ( accumulators::weighted_moment<2>(args) - weighted_mean(args) * weighted_mean(args) )
- * ( accumulators::weighted_moment<2>(args) - weighted_mean(args) * weighted_mean(args) )
- ) - 3.;
- }
- };
- } // namespace impl
- ///////////////////////////////////////////////////////////////////////////////
- // tag::weighted_kurtosis
- //
- namespace tag
- {
- struct weighted_kurtosis
- : depends_on<weighted_mean, weighted_moment<2>, weighted_moment<3>, weighted_moment<4> >
- {
- /// INTERNAL ONLY
- ///
- typedef accumulators::impl::weighted_kurtosis_impl<mpl::_1, mpl::_2> impl;
- };
- }
- ///////////////////////////////////////////////////////////////////////////////
- // extract::weighted_kurtosis
- //
- namespace extract
- {
- extractor<tag::weighted_kurtosis> const weighted_kurtosis = {};
- BOOST_ACCUMULATORS_IGNORE_GLOBAL(weighted_kurtosis)
- }
- using extract::weighted_kurtosis;
- }} // namespace boost::accumulators
- #endif
|