template<class IntType = int> class uniform_int_distribution { public: // types using result_type = IntType; using param_type = unspecified; // constructors and reset functions explicit uniform_int_distribution(IntType a = 0, IntType b = numeric_limits<IntType>::max()); explicit uniform_int_distribution(const param_type& parm); void reset(); // generating functions template<class URBG> result_type operator()(URBG& g); template<class URBG> result_type operator()(URBG& g, const param_type& parm); // property functions result_type a() const; result_type b() const; param_type param() const; void param(const param_type& parm); result_type min() const; result_type max() const; };
explicit uniform_int_distribution(IntType a = 0, IntType b = numeric_limits<IntType>::max());
result_type a() const;
result_type b() const;
template<class RealType = double> class uniform_real_distribution { public: // types using result_type = RealType; using param_type = unspecified; // constructors and reset functions explicit uniform_real_distribution(RealType a = 0.0, RealType b = 1.0); explicit uniform_real_distribution(const param_type& parm); void reset(); // generating functions template<class URBG> result_type operator()(URBG& g); template<class URBG> result_type operator()(URBG& g, const param_type& parm); // property functions result_type a() const; result_type b() const; param_type param() const; void param(const param_type& parm); result_type min() const; result_type max() const; };
explicit uniform_real_distribution(RealType a = 0.0, RealType b = 1.0);
result_type a() const;
result_type b() const;
class bernoulli_distribution { public: // types using result_type = bool; using param_type = unspecified; // constructors and reset functions explicit bernoulli_distribution(double p = 0.5); explicit bernoulli_distribution(const param_type& parm); void reset(); // generating functions template<class URBG> result_type operator()(URBG& g); template<class URBG> result_type operator()(URBG& g, const param_type& parm); // property functions double p() const; param_type param() const; void param(const param_type& parm); result_type min() const; result_type max() const; };
explicit bernoulli_distribution(double p = 0.5);
double p() const;
template<class IntType = int> class binomial_distribution { public: // types using result_type = IntType; using param_type = unspecified; // constructors and reset functions explicit binomial_distribution(IntType t = 1, double p = 0.5); explicit binomial_distribution(const param_type& parm); void reset(); // generating functions template<class URBG> result_type operator()(URBG& g); template<class URBG> result_type operator()(URBG& g, const param_type& parm); // property functions IntType t() const; double p() const; param_type param() const; void param(const param_type& parm); result_type min() const; result_type max() const; };
explicit binomial_distribution(IntType t = 1, double p = 0.5);
IntType t() const;
double p() const;
template<class IntType = int> class geometric_distribution { public: // types using result_type = IntType; using param_type = unspecified; // constructors and reset functions explicit geometric_distribution(double p = 0.5); explicit geometric_distribution(const param_type& parm); void reset(); // generating functions template<class URBG> result_type operator()(URBG& g); template<class URBG> result_type operator()(URBG& g, const param_type& parm); // property functions double p() const; param_type param() const; void param(const param_type& parm); result_type min() const; result_type max() const; };
explicit geometric_distribution(double p = 0.5);
double p() const;
template<class IntType = int> class negative_binomial_distribution { public: // types using result_type = IntType; using param_type = unspecified; // constructor and reset functions explicit negative_binomial_distribution(IntType k = 1, double p = 0.5); explicit negative_binomial_distribution(const param_type& parm); void reset(); // generating functions template<class URBG> result_type operator()(URBG& g); template<class URBG> result_type operator()(URBG& g, const param_type& parm); // property functions IntType k() const; double p() const; param_type param() const; void param(const param_type& parm); result_type min() const; result_type max() const; };
explicit negative_binomial_distribution(IntType k = 1, double p = 0.5);
IntType k() const;
double p() const;
The distribution parameter μ is also known as this distribution's mean.
template<class IntType = int> class poisson_distribution { public: // types using result_type = IntType; using param_type = unspecified; // constructors and reset functions explicit poisson_distribution(double mean = 1.0); explicit poisson_distribution(const param_type& parm); void reset(); // generating functions template<class URBG> result_type operator()(URBG& g); template<class URBG> result_type operator()(URBG& 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; };
explicit poisson_distribution(double mean = 1.0);
double mean() const;
template<class RealType = double> class exponential_distribution { public: // types using result_type = RealType; using param_type = unspecified; // constructors and reset functions explicit exponential_distribution(RealType lambda = 1.0); explicit exponential_distribution(const param_type& parm); void reset(); // generating functions template<class URBG> result_type operator()(URBG& g); template<class URBG> result_type operator()(URBG& 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; };
explicit exponential_distribution(RealType lambda = 1.0);
RealType lambda() const;
template<class RealType = double> class gamma_distribution { public: // types using result_type = RealType; using param_type = unspecified; // 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 URBG> result_type operator()(URBG& g); template<class URBG> result_type operator()(URBG& 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);
RealType alpha() const;
RealType beta() const;
template<class RealType = double> class weibull_distribution { public: // types using result_type = RealType; using param_type = unspecified; // 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 URBG> result_type operator()(URBG& g); template<class URBG> result_type operator()(URBG& 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);
RealType a() const;
RealType b() const;
template<class RealType = double> class extreme_value_distribution { public: // types using result_type = RealType; using param_type = unspecified; // 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 URBG> result_type operator()(URBG& g); template<class URBG> result_type operator()(URBG& 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);
RealType a() const;
RealType b() const;
The distribution parameters μ and σ are also known as this distribution's mean and standard deviation.
template<class RealType = double> class normal_distribution { public: // types using result_type = RealType; using param_type = unspecified; // constructors and reset functions explicit normal_distribution(RealType mean = 0.0, RealType stddev = 1.0); explicit normal_distribution(const param_type& parm); void reset(); // generating functions template<class URBG> result_type operator()(URBG& g); template<class URBG> result_type operator()(URBG& g, const param_type& parm); // property functions RealType mean() const; RealType stddev() const; param_type param() const; void param(const param_type& parm); result_type min() const; result_type max() const; };
explicit normal_distribution(RealType mean = 0.0, RealType stddev = 1.0);
RealType mean() const;
RealType stddev() const;
template<class RealType = double> class lognormal_distribution { public: // types using result_type = RealType; using param_type = unspecified; // constructor and reset functions explicit lognormal_distribution(RealType m = 0.0, RealType s = 1.0); explicit lognormal_distribution(const param_type& parm); void reset(); // generating functions template<class URBG> result_type operator()(URBG& g); template<class URBG> result_type operator()(URBG& g, const param_type& parm); // property functions RealType m() const; RealType s() const; param_type param() const; void param(const param_type& parm); result_type min() const; result_type max() const; };
explicit lognormal_distribution(RealType m = 0.0, RealType s = 1.0);
RealType m() const;
RealType s() const;
template<class RealType = double> class chi_squared_distribution { public: // types using result_type = RealType; using param_type = unspecified; // constructor and reset functions explicit chi_squared_distribution(RealType n = 1); explicit chi_squared_distribution(const param_type& parm); void reset(); // generating functions template<class URBG> result_type operator()(URBG& g); template<class URBG> result_type operator()(URBG& g, const param_type& parm); // property functions RealType n() const; param_type param() const; void param(const param_type& parm); result_type min() const; result_type max() const; };
explicit chi_squared_distribution(RealType n = 1);
RealType n() const;
template<class RealType = double> class cauchy_distribution { public: // types using result_type = RealType; using param_type = unspecified; // constructor and reset functions explicit cauchy_distribution(RealType a = 0.0, RealType b = 1.0); explicit cauchy_distribution(const param_type& parm); void reset(); // generating functions template<class URBG> result_type operator()(URBG& g); template<class URBG> result_type operator()(URBG& 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 cauchy_distribution(RealType a = 0.0, RealType b = 1.0);
RealType a() const;
RealType b() const;
template<class RealType = double> class fisher_f_distribution { public: // types using result_type = RealType; using param_type = unspecified; // constructor and reset functions explicit fisher_f_distribution(RealType m = 1, RealType n = 1); explicit fisher_f_distribution(const param_type& parm); void reset(); // generating functions template<class URBG> result_type operator()(URBG& g); template<class URBG> result_type operator()(URBG& g, const param_type& parm); // property functions RealType m() const; RealType n() const; param_type param() const; void param(const param_type& parm); result_type min() const; result_type max() const; };
explicit fisher_f_distribution(RealType m = 1, RealType n = 1);
RealType m() const;
RealType n() const;
template<class RealType = double> class student_t_distribution { public: // types using result_type = RealType; using param_type = unspecified; // constructor and reset functions explicit student_t_distribution(RealType n = 1); explicit student_t_distribution(const param_type& parm); void reset(); // generating functions template<class URBG> result_type operator()(URBG& g); template<class URBG> result_type operator()(URBG& g, const param_type& parm); // property functions RealType n() const; param_type param() const; void param(const param_type& parm); result_type min() const; result_type max() const; };
explicit student_t_distribution(RealType n = 1);
RealType n() const;
template<class IntType = int> class discrete_distribution { public: // types using result_type = IntType; using param_type = unspecified; // constructor and reset functions discrete_distribution(); template<class InputIterator> discrete_distribution(InputIterator firstW, InputIterator lastW); discrete_distribution(initializer_list<double> wl); template<class UnaryOperation> discrete_distribution(size_t nw, double xmin, double xmax, UnaryOperation fw); explicit discrete_distribution(const param_type& parm); void reset(); // generating functions template<class URBG> result_type operator()(URBG& g); template<class URBG> result_type operator()(URBG& g, const param_type& parm); // property functions vector<double> probabilities() const; param_type param() const; void param(const param_type& parm); result_type min() const; result_type max() const; };
discrete_distribution();
template<class InputIterator>
discrete_distribution(InputIterator firstW, InputIterator lastW);
discrete_distribution(initializer_list<double> wl);
template<class UnaryOperation>
discrete_distribution(size_t nw, double xmin, double xmax, UnaryOperation fw);
vector<double> probabilities() const;
in which the values , commonly known as the weights, shall be non-negative, non-NaN, and non-infinity.
template<class RealType = double> class piecewise_constant_distribution { public: // types using result_type = RealType; using param_type = unspecified; // constructor and reset functions piecewise_constant_distribution(); template<class InputIteratorB, class InputIteratorW> piecewise_constant_distribution(InputIteratorB firstB, InputIteratorB lastB, InputIteratorW firstW); template<class UnaryOperation> piecewise_constant_distribution(initializer_list<RealType> bl, UnaryOperation fw); template<class UnaryOperation> piecewise_constant_distribution(size_t nw, RealType xmin, RealType xmax, UnaryOperation fw); explicit piecewise_constant_distribution(const param_type& parm); void reset(); // generating functions template<class URBG> result_type operator()(URBG& g); template<class URBG> result_type operator()(URBG& g, const param_type& parm); // property functions vector<result_type> intervals() const; vector<result_type> densities() const; param_type param() const; void param(const param_type& parm); result_type min() const; result_type max() const; };
piecewise_constant_distribution();
template<class InputIteratorB, class InputIteratorW>
piecewise_constant_distribution(InputIteratorB firstB, InputIteratorB lastB,
InputIteratorW firstW);
template<class UnaryOperation>
piecewise_constant_distribution(initializer_list<RealType> bl, UnaryOperation fw);
template<class UnaryOperation>
piecewise_constant_distribution(size_t nw, RealType xmin, RealType xmax, UnaryOperation fw);
vector<result_type> intervals() const;
vector<result_type> densities() const;
template<class RealType = double> class piecewise_linear_distribution { public: // types using result_type = RealType; using param_type = unspecified; // constructor and reset functions piecewise_linear_distribution(); template<class InputIteratorB, class InputIteratorW> piecewise_linear_distribution(InputIteratorB firstB, InputIteratorB lastB, InputIteratorW firstW); template<class UnaryOperation> piecewise_linear_distribution(initializer_list<RealType> bl, UnaryOperation fw); template<class UnaryOperation> piecewise_linear_distribution(size_t nw, RealType xmin, RealType xmax, UnaryOperation fw); explicit piecewise_linear_distribution(const param_type& parm); void reset(); // generating functions template<class URBG> result_type operator()(URBG& g); template<class URBG> result_type operator()(URBG& g, const param_type& parm); // property functions vector<result_type> intervals() const; vector<result_type> densities() const; param_type param() const; void param(const param_type& parm); result_type min() const; result_type max() const; };
piecewise_linear_distribution();
template<class InputIteratorB, class InputIteratorW>
piecewise_linear_distribution(InputIteratorB firstB, InputIteratorB lastB,
InputIteratorW firstW);
template<class UnaryOperation>
piecewise_linear_distribution(initializer_list<RealType> bl, UnaryOperation fw);
template<class UnaryOperation>
piecewise_linear_distribution(size_t nw, RealType xmin, RealType xmax, UnaryOperation fw);
vector<result_type> intervals() const;
vector<result_type> densities() const;