/usr/include/boost/accumulators/statistics
NameSizeModeActions
parameters/-0755rm
variates/-0755rm
count.hpp20130644editdlrm
covariance.hpp71370644editdlrm
density.hpp100070644editdlrm
error_of.hpp25880644editdlrm
error_of_mean.hpp21930644editdlrm
extended_p_square.hpp116330644editdlrm
extended_p_square_quantile.hpp125220644editdlrm
kurtosis.hpp38640644editdlrm
max.hpp22940644editdlrm
mean.hpp93340644editdlrm
median.hpp102420644editdlrm
min.hpp22940644editdlrm
moment.hpp34360644editdlrm
peaks_over_threshold.hpp175250644editdlrm
pot_quantile.hpp73360644editdlrm
pot_tail_mean.hpp78020644editdlrm
p_square_cumulative_distribution.hpp9550644editdlrm
p_square_cumul_dist.hpp103650644editdlrm
p_square_quantile.hpp100860644editdlrm
rolling_count.hpp25740644editdlrm
rolling_mean.hpp67530644editdlrm
rolling_moment.hpp37410644editdlrm
rolling_sum.hpp28710644editdlrm
rolling_variance.hpp94860644editdlrm
rolling_window.hpp72540644editdlrm
skewness.hpp36910644editdlrm
stats.hpp9720644editdlrm
sum.hpp38840644editdlrm
sum_kahan.hpp51040644editdlrm
tail.hpp110120644editdlrm
tail_mean.hpp91580644editdlrm
tail_quantile.hpp55350644editdlrm
tail_variate.hpp45040644editdlrm
tail_variate_means.hpp104630644editdlrm
times2_iterator.hpp19650644editdlrm
variance.hpp75220644editdlrm
weighted_covariance.hpp52440644editdlrm
weighted_density.hpp95180644editdlrm
weighted_extended_p_square.hpp128420644editdlrm
weighted_kurtosis.hpp41470644editdlrm
weighted_mean.hpp66370644editdlrm
weighted_median.hpp86670644editdlrm
weighted_moment.hpp33840644editdlrm
weighted_peaks_over_threshold.hpp123520644editdlrm
weighted_p_square_cumulative_distribution.hpp10090644editdlrm
weighted_p_square_cumul_dist.hpp110580644editdlrm
weighted_p_square_quantile.hpp111100644editdlrm
weighted_skewness.hpp38440644editdlrm
weighted_sum.hpp36390644editdlrm
weighted_sum_kahan.hpp45590644editdlrm
weighted_tail_mean.hpp57880644editdlrm
weighted_tail_quantile.hpp51350644editdlrm
weighted_tail_variate_means.hpp100520644editdlrm
weighted_variance.hpp67740644editdlrm
with_error.hpp12770644editdlrm
Edit: /usr/include/boost/accumulators/statistics/variance.hpp (7522B)
/////////////////////////////////////////////////////////////////////////////// // variance.hpp // // Copyright 2005 Daniel Egloff, Eric Niebler. 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_VARIANCE_HPP_EAN_28_10_2005 #define BOOST_ACCUMULATORS_STATISTICS_VARIANCE_HPP_EAN_28_10_2005 #include #include #include #include #include #include #include #include #include #include #include namespace boost { namespace accumulators { namespace impl { //! Lazy calculation of variance. /*! Default sample variance implementation based on the second moment \f$ M_n^{(2)} \f$ moment<2>, mean and count. \f[ \sigma_n^2 = M_n^{(2)} - \mu_n^2. \f] where \f[ \mu_n = \frac{1}{n} \sum_{i = 1}^n x_i. \f] is the estimate of the sample mean and \f$n\f$ is the number of samples. */ template struct lazy_variance_impl : accumulator_base { // for boost::result_of typedef typename numeric::functional::fdiv::result_type result_type; lazy_variance_impl(dont_care) {} template result_type result(Args const &args) const { extractor mean; result_type tmp = mean(args); return accumulators::moment<2>(args) - tmp * tmp; } // serialization is done by accumulators it depends on template void serialize(Archive & ar, const unsigned int file_version) {} }; //! Iterative calculation of variance. /*! Iterative calculation of sample variance \f$\sigma_n^2\f$ according to the formula \f[ \sigma_n^2 = \frac{1}{n} \sum_{i = 1}^n (x_i - \mu_n)^2 = \frac{n-1}{n} \sigma_{n-1}^2 + \frac{1}{n-1}(x_n - \mu_n)^2. \f] where \f[ \mu_n = \frac{1}{n} \sum_{i = 1}^n x_i. \f] is the estimate of the sample mean and \f$n\f$ is the number of samples. Note that the sample variance is not defined for \f$n <= 1\f$. A simplification can be obtained by the approximate recursion \f[ \sigma_n^2 \approx \frac{n-1}{n} \sigma_{n-1}^2 + \frac{1}{n}(x_n - \mu_n)^2. \f] because the difference \f[ \left(\frac{1}{n-1} - \frac{1}{n}\right)(x_n - \mu_n)^2 = \frac{1}{n(n-1)}(x_n - \mu_n)^2. \f] converges to zero as \f$n \rightarrow \infty\f$. However, for small \f$ n \f$ the difference can be non-negligible. */ template struct variance_impl : accumulator_base { // for boost::result_of typedef typename numeric::functional::fdiv::result_type result_type; template variance_impl(Args const &args) : variance(numeric::fdiv(args[sample | Sample()], numeric::one::value)) { } template void operator ()(Args const &args) { std::size_t cnt = count(args); if(cnt > 1) { extractor mean; result_type tmp = args[parameter::keyword::get()] - mean(args); this->variance = numeric::fdiv(this->variance * (cnt - 1), cnt) + numeric::fdiv(tmp * tmp, cnt - 1); } } result_type result(dont_care) const { return this->variance; } // make this accumulator serializeable template void serialize(Archive & ar, const unsigned int file_version) { ar & variance; } private: result_type variance; }; } // namespace impl /////////////////////////////////////////////////////////////////////////////// // tag::variance // tag::immediate_variance // namespace tag { struct lazy_variance : depends_on, mean> { /// INTERNAL ONLY /// typedef accumulators::impl::lazy_variance_impl impl; }; struct variance : depends_on { /// INTERNAL ONLY /// typedef accumulators::impl::variance_impl impl; }; } /////////////////////////////////////////////////////////////////////////////// // extract::lazy_variance // extract::variance // namespace extract { extractor const lazy_variance = {}; extractor const variance = {}; BOOST_ACCUMULATORS_IGNORE_GLOBAL(lazy_variance) BOOST_ACCUMULATORS_IGNORE_GLOBAL(variance) } using extract::lazy_variance; using extract::variance; // variance(lazy) -> lazy_variance template<> struct as_feature { typedef tag::lazy_variance type; }; // variance(immediate) -> variance template<> struct as_feature { typedef tag::variance type; }; // for the purposes of feature-based dependency resolution, // immediate_variance provides the same feature as variance template<> struct feature_of : feature_of { }; // So that variance can be automatically substituted with // weighted_variance when the weight parameter is non-void. template<> struct as_weighted_feature { typedef tag::weighted_variance type; }; // for the purposes of feature-based dependency resolution, // weighted_variance provides the same feature as variance template<> struct feature_of : feature_of { }; // So that immediate_variance can be automatically substituted with // immediate_weighted_variance when the weight parameter is non-void. template<> struct as_weighted_feature { typedef tag::lazy_weighted_variance type; }; // for the purposes of feature-based dependency resolution, // immediate_weighted_variance provides the same feature as immediate_variance template<> struct feature_of : feature_of { }; //////////////////////////////////////////////////////////////////////////// //// droppable_accumulator //// need to specialize droppable lazy variance to cache the result at the //// point the accumulator is dropped. ///// INTERNAL ONLY ///// //template //struct droppable_accumulator > // : droppable_accumulator_base< // with_cached_result > // > //{ // template // droppable_accumulator(Args const &args) // : droppable_accumulator::base(args) // { // } //}; }} // namespace boost::accumulators #endif