negative_binomial_distribution 類別

產生負二項式分佈。

template<class IntType = int> class negative_binomial_distribution { public:     // types     typedef IntType result_type;     struct param_type;     // 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 URNG>     result_type operator()(URNG& gen);     template<class URNG>     result_type operator()(URNG& gen, 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; };

參數

• IntType
  整數結果類型，預設值為 int。 如需可能的類型，請參閱 <random>。

備註

此範本類別描述產生使用者指定之整數類型的值的分佈 (若無提供則為 int 類型)，而這是根據負二項式分佈離散可能性函式進行分佈。 下表提供各個成員的文章連結。

negative_binomial_distribution::negative_binomial_distribution	negative_binomial_distribution::k	negative_binomial_distribution::param
negative_binomial_distribution::operator()	negative_binomial_distribution::p	negative_binomial_distribution::param_type

屬性成員 k() 和 p() 會分別傳回目前儲存的分佈參數值 k 和 p。

如需分佈類別及其成員的詳細資訊，請參閱 <random>。

如需負二項式分佈離散可能性函式的詳細資訊，請參閱 Wolfram MathWorld 文章：負二項式分佈 (英文)。

範例

 

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

void test(const int k, const double p, const int& s) {

    // uncomment to use a non-deterministic seed
    //    std::random_device rd;
    //    std::mt19937 gen(rd());
    std::mt19937 gen(1729);

    std::negative_binomial_distribution<> distr(k, p);

    std::cout << std::endl;
    std::cout << "k == " << distr.k() << std::endl;
    std::cout << "p == " << distr.p() << std::endl;

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

    // print results
    std::cout << "Histogram for " << s << " samples:" << std::endl;
    for (const auto& elem : histogram) {
        std::cout << std::setw(5) << elem.first << ' ' << std::string(elem.second, ':') << std::endl;
    }
    std::cout << std::endl;
}

int main()
{
    int    k_dist = 1;
    double p_dist = 0.5;
    int    samples = 100;

    std::cout << "Use CTRL-Z to bypass data entry and run using default values." << std::endl;
    std::cout << "Enter an integer value for k distribution (where 0 < k): ";
    std::cin >> k_dist;
    std::cout << "Enter a double value for p distribution (where 0.0 < p <= 1.0): ";
    std::cin >> p_dist;
    std::cout << "Enter an integer value for a sample count: ";
    std::cin >> samples;

    test(k_dist, p_dist, samples);
}

輸出

第一次執行：

Use CTRL-Z to bypass data entry and run using default values.
Enter an integer value for k distribution (where 0 < k): 1
Enter a double value for p distribution (where 0.0 < p <= 1.0): .5
Enter an integer value for a sample count: 100

k == 1
p == 0.5
Histogram for 100 samples:
    0 :::::::::::::::::::::::::::::::::::::::::::
    1 ::::::::::::::::::::::::::::::::
    2 ::::::::::::
    3 :::::::
    4 ::::
    5 ::

第二次執行：

Use CTRL-Z to bypass data entry and run using default values.
Enter an integer value for k distribution (where 0 < k): 100
Enter a double value for p distribution (where 0.0 < p <= 1.0): .667
Enter an integer value for a sample count: 100

k == 100
p == 0.667
Histogram for 100 samples:
   31 ::
   32 :
   33 ::
   34 :
   35 ::
   37 ::
   38 :
   39 :
   40 ::
   41 :::
   42 :::
   43 :::::
   44 :::::
   45 ::::
   46 ::::::
   47 ::::::::
   48 :::
   49 :::
   50 :::::::::
   51 :::::::
   52 ::
   53 :::
   54 :::::
   56 ::::
   58 :
   59 :::::
   60 ::
   61 :
   62 ::
   64 :
   69 ::::

需求

標頭：<random>

命名空間: std

請參閱

參考

<random>