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## Struct template p_square_quantile_impl

boost::accumulators::impl::p_square_quantile_impl — Single quantile estimation with the algorithm.

## Synopsis

    // In header: <boost/accumulators/statistics/p_square_quantile.hpp>

    template<typename Sample, typename Impl>
    struct p_square_quantile_impl {
      // types
      typedef numeric::functional::average< Sample, std::size_t >::result_type float_type;
      typedef array< float_type, 5 >                                           array_type;
      typedef float_type                                                       result_type;

      // construct/copy/destruct
      template<typename Args> p_square_quantile_impl(Args const &);

      // public member functions
      template<typename Args> void operator()(Args const &);
      result_type result(dont_care) const;
    };

## Description

The algorithm estimates a quantile dynamically without storing samples. Instead of storing the whole sample cumulative distribution, only five points (markers) are stored. The heights of these markers are the minimum and the maximum of the samples and the current estimates of the -, - and -quantiles. Their positions are equal to the number of samples that are smaller or equal to the markers. Each time a new samples is recorded, the positions of the markers are updated and if necessary their heights are adjusted using a piecewise- parabolic formula.

For further details, see

R. Jain and I. Chlamtac, The P^2 algorithmus fordynamic calculation of quantiles and histograms without storing observations, Communications of the ACM, Volume 28 (October), Number 10, 1985, p. 1076-1085.

### `p_square_quantile_impl` public construct/copy/destruct

1.     template<typename Args> p_square_quantile_impl(Args const & args);

### `p_square_quantile_impl` public member functions

1.     template<typename Args> void operator()(Args const & args);

2.     result_type result(dont_care) const;