...one of the most highly
regarded and expertly designed C++ library projects in the
world.
— Herb Sutter and Andrei
Alexandrescu, C++
Coding Standards
boost::histogram::utility::clopper_pearson_interval — ClopperPearson interval.
// In header: <boost/histogram/utility/clopper_pearson_interval.hpp> template<typename ValueType> class clopper_pearson_interval : public boost::histogram::utility::binomial_proportion_interval< ValueType > { public: // types typedef typename clopper_pearson_interval::value_type value_type; typedef typename clopper_pearson_interval::interval_type interval_type; // construct/copy/destruct explicit clopper_pearson_interval(confidence_level = deviation{1}) noexcept; // public member functions interval_type operator()(value_type, value_type) const noexcept; };
This is the classic frequentist interval obtained with the Neyman construction. It is therefore often called the 'exact' interval. It is guaranteed to have at least the requested confidence level for all values of the fraction.
The interval is wider than others that produce coverage closer to the expected confidence level over a random ensemble of factions. The ClopperPearson interval essentially always overcovers for such a random ensemble, which is undesirable in practice. The ClopperPearson interval is recommended when it is important to be conservative, but the Wilson interval should be preferred in most applications.
C. Clopper, E.S. Pearson (1934), Biometrika 26 (4): 404413. doi:10.1093/biomet/26.4.404.
clopper_pearson_interval
public
construct/copy/destructexplicit clopper_pearson_interval(confidence_level cl = deviation{1}) noexcept;Construct ClopperPearson interval computer.
Parameters: 
