A poisson_distribution random number distribution produces integer values i ≥ 0 distributed according to the discrete probability function The distribution parameter μ is also known as this distribution's mean.
template<class IntType = int> class poisson_distribution{ public: // types typedef IntType result_type; typedef unspecified param_type; // constructors and reset functions explicit poisson_distribution(double mean = 1.0); explicit poisson_distribution(const param_type& parm); void reset(); // generating functions template<class URNG> result_type operator()(URNG& g); template<class URNG> result_type operator()(URNG& g, const param_type& parm); // property functions double mean() const; param_type param() const; void param(const param_type& parm); result_type min() const; result_type max() const; };
Requires: 0 < mean .
Effects: Constructs a poisson_distribution object; mean corresponds to the parameter of the distribution.
Returns: The value of the mean parameter with which the object was constructed.
An exponential_distribution random number distribution produces random numbers x > 0 distributed according to the probability density function p(x | λ) = λ e-λ x .
template<class RealType = double> class exponential_distribution{ public: // types typedef RealType result_type; typedef unspecified param_type; // constructors and reset functions explicit exponential_distribution(RealType lambda = 1.0); explicit exponential_distribution(const param_type& parm); void reset(); // generating functions template<class URNG> result_type operator()(URNG& g); template<class URNG> result_type operator()(URNG& g, const param_type& parm); // property functions RealType lambda() const; param_type param() const; void param(const param_type& parm); result_type min() const; result_type max() const; };
Requires: 0 < lambda .
Effects: Constructs a exponential_distribution object; lambda corresponds to the parameter of the distribution.
Returns: The value of the lambda parameter with which the object was constructed.
A gamma_distribution random number distribution produces random numbers x > 0 distributed according to the probability density function p(x | α,β) = e-x/β βα · Γ(α) · x α-1 .
template<class RealType = double> class gamma_distribution{ public: // types typedef RealType result_type; typedef unspecified param_type; // constructors and reset functions explicit gamma_distribution(RealType alpha = 1.0, RealType beta = 1.0); explicit gamma_distribution(const param_type& parm); void reset(); // generating functions template<class URNG> result_type operator()(URNG& g); template<class URNG> result_type operator()(URNG& g, const param_type& parm); // property functions RealType alpha() const; RealType beta() const; param_type param() const; void param(const param_type& parm); result_type min() const; result_type max() const; };
explicit gamma_distribution(RealType alpha = 1.0, RealType beta = 1.0);
Requires: 0 < alpha and 0 < beta .
Effects: Constructs a gamma_distribution object; alpha and beta correspond to the parameters of the distribution.
Returns: The value of the alpha parameter with which the object was constructed.
Returns: The value of the beta parameter with which the object was constructed.
A weibull_distribution random number distribution produces random numbers x ≥ 0 distributed according to the probability density function
template<class RealType = double> class weibull_distribution{ public: // types typedef RealType result_type; typedef unspecified param_type; // constructor and reset functions explicit weibull_distribution(RealType a = 1.0, RealType b = 1.0) explicit weibull_distribution(const param_type& parm); void reset(); // generating functions template<class URNG> result_type operator()(URNG& g); template<class URNG> result_type operator()(URNG& g, const param_type& parm); // property functions RealType a() const; RealType b() const; param_type param() const; void param(const param_type& parm); result_type min() const; result_type max() const; };
explicit weibull_distribution(RealType a = 1.0, RealType b = 1.0);
Requires: 0 < a and 0 < b .
Effects: Constructs a weibull_distribution object; a and b correspond to the respective parameters of the distribution.
Returns: The value of the a parameter with which the object was constructed.
Returns: The value of the b parameter with which the object was constructed.
An extreme_value_distribution random number distribution produces random numbers x distributed according to the probability density function280
template<class RealType = double> class extreme_value_distribution{ public: // types typedef RealType result_type; typedef unspecified param_type; // constructor and reset functions explicit extreme_value_distribution(RealType a = 0.0, RealType b = 1.0); explicit extreme_value_distribution(const param_type& parm); void reset(); // generating functions template<class URNG> result_type operator()(URNG& g); template<class URNG> result_type operator()(URNG& g, const param_type& parm); // property functions RealType a() const; RealType b() const; param_type param() const; void param(const param_type& parm); result_type min() const; result_type max() const; };
explicit extreme_value_distribution(RealType a = 0.0, RealType b = 1.0);
Requires: 0 < b .
Effects: Constructs an extreme_value_distribution object; a and b correspond to the respective parameters of the distribution.
Returns: The value of the a parameter with which the object was constructed.
Returns: The value of the b parameter with which the object was constructed.
The distribution corresponding to this probability density function is also known (with a possible change of variable) as the Gumbel Type I, the log-Weibull, or the Fisher-Tippett Type I distribution.