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## Struct template extended_p_square_impl

boost::accumulators::impl::extended_p_square_impl — Multiple quantile estimation with the extended algorithm.

## Synopsis

    template<typename Sample>
    struct extended_p_square_impl {
      // types
      typedef numeric::functional::average< Sample, std::size_t >::result_type float_type;
      typedef std::vector< float_type >                                        array_type;
      typedef unspecified                                                      result_type;

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

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

## Description

Extended algorithm for estimation of several quantiles without storing samples. Assume that quantiles are to be estimated. Instead of storing the whole sample cumulative distribution, the algorithm maintains only principal markers and middle markers, whose positions are updated with each sample and whose heights are adjusted (if necessary) using a piecewise-parablic formula. The heights of these central markers are the current estimates of the quantiles and returned as an iterator range.

For further details, see

K. E. E. Raatikainen, Simultaneous estimation of several quantiles, Simulation, Volume 49, Number 4 (October), 1986, p. 159-164.

The extended algorithm generalizess the algorithm of

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

### `extended_p_square_impl` public construct/copy/destruct

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

### `extended_p_square_impl` public member functions

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

2.     result_type result(dont_care) const;