oneapi::mkl::rng::negative_binomial

Generates random numbers with negative binomial distribution.

Description

The oneapi::mkl::rng::negative_binomial class object is used in the oneapi::mkl::rng::generate function to provide random numbers with negative binomial distribution and distribution parameters a and p, where p, aR; 0 < p < 1; a > 0.

If the first distribution parameter aN, this distribution is the same as Pascal distribution. If aN, the distribution can be interpreted as the expected time of a-th success in a sequence of Bernoulli trials, when the probability of success is p.

The probability distribution is given by:

\[P(X = k) = C_{a+k-1}^k p^a (1-p)^k, k \in \{0, 1, 2, \ldots\}\]

The cumulative distribution function is as follows:

\[\begin{split}F_{a, p}(x) = \begin{cases} \sum_{k=0}^{\lfloor x \rfloor} C_{a + k - 1}^{k} p^a (1-p)^k, & x \geq 0 \\ 0, & x < 0 \end{cases}, x \in R\end{split}\]

Product and Performance Information

Performance varies by use, configuration and other factors. Learn more at https://www.intel.com/PerformanceIndex. Notice revision #20201201

API

Syntax

template<typename IntType = std::int32_t, typename Method = negative_binomial_method::by_default>
class negative_binomial {
public:
  using method_type = Method;
  using result_type = IntType;
  negative_binomial(): negative_binomial(0.1, 0.5){}
  explicit negative_binomial(double a, double p);
  explicit negative_binomial(const param_type& pt);
  double a() const;
  double p() const;
  param_type param() const;
  void param(const param_type& pt);
};

Devices supported: CPU and GPU

Include Files

  • oneapi/mkl/rng.hpp

Template Parameters

typename IntType = std::int32_t

Type of the produced values. The specific values are as follows:

std::int32_t

std::uint32_t

typename Method =  oneapi::mkl::rng::negative_binomial_method::by_default

Generation method. The specific values are as follows:

oneapi::mkl::rng::negative_binomial_method::nbar

See brief descriptions of the methods in Distributions Template Parameter Method.

Input Parameters

Name

Type

Description

a

double

The first distribution parameter a.

p

double

The second distribution parameter p.