StatisticalAlgorithms.hpp File Reference

Tools for statistical analysis. More...

#include <cmath>
#include <numeric>
#include <optional>
#include <iterator>

Go to the source code of this file.

Classes
struct	sequoia::maths::bias::gaussian_approx_estimator

Functions
template<std::input_iterator Iter, class T = typename std::iterator_traits<Iter>::value_type>
std::optional< T >	sequoia::maths::mean (Iter first, Iter last)
template<std::input_iterator Iter, class T = typename std::iterator_traits<Iter>::value_type>
std::pair< std::optional< T >, std::optional< T > >	sequoia::maths::cummulative_square_diffs (Iter first, Iter last)
template<std::input_iterator Iter, class T = typename std::iterator_traits<Iter>::value_type>
std::pair< std::optional< T >, std::optional< T > >	sequoia::maths::variance (Iter first, Iter last)
template<std::input_iterator Iter, class T = typename std::iterator_traits<Iter>::value_type>
std::pair< std::optional< T >, std::optional< T > >	sequoia::maths::sample_variance (Iter first, Iter last)
template<std::input_iterator Iter, class T = typename std::iterator_traits<Iter>::value_type>
std::pair< std::optional< T >, std::optional< T > >	sequoia::maths::standard_deviation (Iter first, Iter last)
template<std::input_iterator Iter, class Estimator = bias::gaussian_approx_estimator, class T = typename std::iterator_traits<Iter>::value_type>
std::pair< std::optional< T >, std::optional< T > >	sequoia::maths::sample_standard_deviation (Iter first, Iter last, Estimator estimator=Estimator{})

Detailed Description

Tools for statistical analysis.