student_t_distribution Class

Generates a Student's t-distribution.

template<class RealType = double>
class student_t_distribution
{
public:
    // types
    typedef RealType result_type;
    struct param_type;
    // constructor and reset functions
    explicit student_t_distribution(RealType n = 1.0);
    explicit student_t_distribution(const param_type& parm);
    void reset();
    // generating functions
    template<class URNG>
    result_type operator()(URNG& gen);
    template<class URNG>
    result_type operator()(URNG& gen, 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;
};

Parameters

• RealType
  The floating-point result type, defaults to double. For possible types, see <random>.

Remarks

The template class describes a distribution that produces values of a user-specified integral type, or type double if none is provided, distributed according to the Student's t-Distribution. The following table links to articles about individual members.

student_t_distribution::student_t_distribution	student_t_distribution::n	student_t_distribution::param
student_t_distribution::operator()		student_t_distribution::param_type

The property function n() returns the value for the stored distribution parameter n.

For more information about distribution classes and their members, see <random>.

For detailed information about the Student's t-distribution, see the Wolfram MathWorld article Students t-Distribution.

Example

 

// compile with: /EHsc /W4
#include <random> 
#include <iostream>
#include <iomanip>
#include <string>
#include <map>

void test(const double n, const int s) {

    // uncomment to use a non-deterministic generator
    //    std::random_device gen;
    std::mt19937 gen(1701);

    std::student_t_distribution<> distr(n);

    std::cout << std::endl;
    std::cout << "min() == " << distr.min() << std::endl;
    std::cout << "max() == " << distr.max() << std::endl;
    std::cout << "n() == " << std::fixed << std::setw(11) << std::setprecision(10) << distr.n() << std::endl;

    // generate the distribution as a histogram
    std::map<double, int> histogram;
    for (int i = 0; i < s; ++i) {
        ++histogram[distr(gen)];
    }

    // print results
    std::cout << "Distribution for " << s << " samples:" << std::endl;
    int counter = 0;
    for (const auto& elem : histogram) {
        std::cout << std::fixed << std::setw(11) << ++counter << ": "
            << std::setw(14) << std::setprecision(10) << elem.first << std::endl;
    }
    std::cout << std::endl;
}

int main()
{
    double n_dist = 0.5;
    int samples = 10;

    std::cout << "Use CTRL-Z to bypass data entry and run using default values." << std::endl;
    std::cout << "Enter a floating point value for the 'n' distribution parameter (must be greater than zero): ";
    std::cin >> n_dist;
    std::cout << "Enter an integer value for the sample count: ";
    std::cin >> samples;

    test(n_dist, samples);
}

Output

Use CTRL-Z to bypass data entry and run using default values.
Enter a floating point value for the 'n' distribution parameter (must be greater than zero): 1
Enter an integer value for the sample count: 10

min() == -1.79769e+308
max() == 1.79769e+308
n() == 1.0000000000
Distribution for 10 samples:
          1:  -1.3084956212
          2:  -1.0899518684
          3:  -0.9568771388
          4:  -0.9372088821
          5:  -0.7381334669
          6:  -0.2488074854
          7:  -0.2028714601
          8:   1.4013074495
          9:   5.3244792236
         10:  92.7084335614

Requirements

Header: <random>

Namespace: std

See Also

Reference

<random>