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Coding Standards
boost::random::poisson_distribution
// In header: <boost/random/poisson_distribution.hpp> template<typename IntType = int, typename RealType = double> class poisson_distribution { public: // types typedef IntType result_type; typedef RealType input_type; // member classes/structs/unions class param_type { public: // types typedef poisson_distribution distribution_type; // public member functions explicit param_type(RealType = 1); RealType mean() const; // friend functions template<typename CharT, typename Traits> std::basic_ostream< CharT, Traits > & operator<<(std::basic_ostream< CharT, Traits > &, const param_type &); template<typename CharT, typename Traits> std::basic_istream< CharT, Traits > & operator>>(std::basic_istream< CharT, Traits > &, param_type &); bool operator==(const param_type &, const param_type &); bool operator!=(const param_type &, const param_type &); }; // public member functions explicit poisson_distribution(RealType = 1); explicit poisson_distribution(const param_type &); template<typename URNG> IntType operator()(URNG &) const; template<typename URNG> IntType operator()(URNG &, const param_type &) const; RealType mean() const; IntType min() const; IntType max() const; param_type param() const; void param(const param_type &); void reset(); // friend functions template<typename CharT, typename Traits> std::basic_ostream< CharT, Traits > & operator<<(std::basic_ostream< CharT, Traits > &, const poisson_distribution &); template<typename CharT, typename Traits> std::basic_istream< CharT, Traits > & operator>>(std::basic_istream< CharT, Traits > &, poisson_distribution &); bool operator==(const poisson_distribution &, const poisson_distribution &); bool operator!=(const poisson_distribution &, const poisson_distribution &); };
An instantiation of the class template poisson_distribution
is a model of random distribution . The poisson distribution has
This implementation is based on the PTRD algorithm described
"The transformed rejection method for generating Poisson random variables", Wolfgang Hormann, Insurance: Mathematics and Economics Volume 12, Issue 1, February 1993, Pages 39-45
poisson_distribution
public member functionsexplicit poisson_distribution(RealType mean = 1);
Constructs a poisson_distribution
with the parameter mean
.
Requires: mean > 0
explicit poisson_distribution(const param_type & param);
Construct an poisson_distribution
object from the parameters.
template<typename URNG> IntType operator()(URNG & urng) const;
Returns a random variate distributed according to the poisson distribution.
template<typename URNG> IntType operator()(URNG & urng, const param_type & param) const;
Returns a random variate distributed according to the poisson distribution with parameters specified by param.
RealType mean() const;
Returns the "mean" parameter of the distribution.
IntType min() const;
Returns the smallest value that the distribution can produce.
IntType max() const;
Returns the largest value that the distribution can produce.
param_type param() const;
Returns the parameters of the distribution.
void param(const param_type & param);
Sets parameters of the distribution.
void reset();
Effects: Subsequent uses of the distribution do not depend on values produced by any engine prior to invoking reset.
poisson_distribution
friend functionstemplate<typename CharT, typename Traits> std::basic_ostream< CharT, Traits > & operator<<(std::basic_ostream< CharT, Traits > & os, const poisson_distribution & pd);
Writes the parameters of the distribution to a std::ostream
.
template<typename CharT, typename Traits> std::basic_istream< CharT, Traits > & operator>>(std::basic_istream< CharT, Traits > & is, poisson_distribution & pd);
Reads the parameters of the distribution from a std::istream
.
bool operator==(const poisson_distribution & lhs, const poisson_distribution & rhs);
Returns true if the two distributions will produce the same sequence of values, given equal generators.
bool operator!=(const poisson_distribution & lhs, const poisson_distribution & rhs);
Returns true if the two distributions could produce different sequences of values, given equal generators.