ecency-mobile/ios/Pods/boost-for-react-native/boost/random/negative_binomial_distribution.hpp

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/* boost random/negative_binomial_distribution.hpp header file
*
* Copyright Steven Watanabe 2010
* 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)
*
* See http://www.boost.org for most recent version including documentation.
*
* $Id$
*/
#ifndef BOOST_RANDOM_NEGATIVE_BINOMIAL_DISTRIBUTION_HPP_INCLUDED
#define BOOST_RANDOM_NEGATIVE_BINOMIAL_DISTRIBUTION_HPP_INCLUDED
#include <iosfwd>
#include <boost/limits.hpp>
#include <boost/random/detail/config.hpp>
#include <boost/random/gamma_distribution.hpp>
#include <boost/random/poisson_distribution.hpp>
namespace boost {
namespace random {
/**
* The negative binomial distribution is an integer valued
* distribution with two parameters, @c k and @c p. The
* distribution produces non-negative values.
*
* The distribution function is
* \f$\displaystyle P(i) = {k+i-1\choose i}p^k(1-p)^i\f$.
*
* This implementation uses a gamma-poisson mixture.
*/
template<class IntType = int, class RealType = double>
class negative_binomial_distribution {
public:
typedef IntType result_type;
typedef RealType input_type;
class param_type {
public:
typedef negative_binomial_distribution distribution_type;
/**
* Construct a param_type object. @c k and @c p
* are the parameters of the distribution.
*
* Requires: k >=0 && 0 <= p <= 1
*/
explicit param_type(IntType k_arg = 1, RealType p_arg = RealType (0.5))
: _k(k_arg), _p(p_arg)
{}
/** Returns the @c k parameter of the distribution. */
IntType k() const { return _k; }
/** Returns the @c p parameter of the distribution. */
RealType p() const { return _p; }
#ifndef BOOST_RANDOM_NO_STREAM_OPERATORS
/** Writes the parameters of the distribution to a @c std::ostream. */
template<class CharT, class Traits>
friend std::basic_ostream<CharT,Traits>&
operator<<(std::basic_ostream<CharT,Traits>& os,
const param_type& parm)
{
os << parm._p << " " << parm._k;
return os;
}
/** Reads the parameters of the distribution from a @c std::istream. */
template<class CharT, class Traits>
friend std::basic_istream<CharT,Traits>&
operator>>(std::basic_istream<CharT,Traits>& is, param_type& parm)
{
is >> parm._p >> std::ws >> parm._k;
return is;
}
#endif
/** Returns true if the parameters have the same values. */
friend bool operator==(const param_type& lhs, const param_type& rhs)
{
return lhs._k == rhs._k && lhs._p == rhs._p;
}
/** Returns true if the parameters have different values. */
friend bool operator!=(const param_type& lhs, const param_type& rhs)
{
return !(lhs == rhs);
}
private:
IntType _k;
RealType _p;
};
/**
* Construct a @c negative_binomial_distribution object. @c k and @c p
* are the parameters of the distribution.
*
* Requires: k >=0 && 0 <= p <= 1
*/
explicit negative_binomial_distribution(IntType k_arg = 1,
RealType p_arg = RealType(0.5))
: _k(k_arg), _p(p_arg)
{}
/**
* Construct an @c negative_binomial_distribution object from the
* parameters.
*/
explicit negative_binomial_distribution(const param_type& parm)
: _k(parm.k()), _p(parm.p())
{}
/**
* Returns a random variate distributed according to the
* negative binomial distribution.
*/
template<class URNG>
IntType operator()(URNG& urng) const
{
gamma_distribution<RealType> gamma(_k, (1-_p)/_p);
poisson_distribution<IntType, RealType> poisson(gamma(urng));
return poisson(urng);
}
/**
* Returns a random variate distributed according to the negative
* binomial distribution with parameters specified by @c param.
*/
template<class URNG>
IntType operator()(URNG& urng, const param_type& parm) const
{
return negative_binomial_distribution(parm)(urng);
}
/** Returns the @c k parameter of the distribution. */
IntType k() const { return _k; }
/** Returns the @c p parameter of the distribution. */
RealType p() const { return _p; }
/** Returns the smallest value that the distribution can produce. */
IntType min BOOST_PREVENT_MACRO_SUBSTITUTION() const { return 0; }
/** Returns the largest value that the distribution can produce. */
IntType max BOOST_PREVENT_MACRO_SUBSTITUTION() const
{ return (std::numeric_limits<IntType>::max)(); }
/** Returns the parameters of the distribution. */
param_type param() const { return param_type(_k, _p); }
/** Sets parameters of the distribution. */
void param(const param_type& parm)
{
_k = parm.k();
_p = parm.p();
}
/**
* Effects: Subsequent uses of the distribution do not depend
* on values produced by any engine prior to invoking reset.
*/
void reset() { }
#ifndef BOOST_RANDOM_NO_STREAM_OPERATORS
/** Writes the parameters of the distribution to a @c std::ostream. */
template<class CharT, class Traits>
friend std::basic_ostream<CharT,Traits>&
operator<<(std::basic_ostream<CharT,Traits>& os,
const negative_binomial_distribution& bd)
{
os << bd.param();
return os;
}
/** Reads the parameters of the distribution from a @c std::istream. */
template<class CharT, class Traits>
friend std::basic_istream<CharT,Traits>&
operator>>(std::basic_istream<CharT,Traits>& is,
negative_binomial_distribution& bd)
{
bd.read(is);
return is;
}
#endif
/** Returns true if the two distributions will produce the same
sequence of values, given equal generators. */
friend bool operator==(const negative_binomial_distribution& lhs,
const negative_binomial_distribution& rhs)
{
return lhs._k == rhs._k && lhs._p == rhs._p;
}
/** Returns true if the two distributions could produce different
sequences of values, given equal generators. */
friend bool operator!=(const negative_binomial_distribution& lhs,
const negative_binomial_distribution& rhs)
{
return !(lhs == rhs);
}
private:
/// @cond \show_private
template<class CharT, class Traits>
void read(std::basic_istream<CharT, Traits>& is) {
param_type parm;
if(is >> parm) {
param(parm);
}
}
// parameters
IntType _k;
RealType _p;
/// @endcond
};
}
}
#endif