oneapi::mkl::rng::device::exponential

Generates exponentially distributed random numbers.

Description

The oneapi::mkl::rng::device::exponential class object is used in the oneapi::mkl::rng::device::generate function to provide random numbers with exponential distribution that has displacement \(a\) and scalefactor \(\beta\), where \(a, \beta \in R ; \beta > 0\).

The probability density function is given by:

\[\begin{split}f_{a, \beta}(x) = \begin{cases} \frac{1}{\beta} \exp (-\frac{(x-a)}{\beta}), & x \geq a \\ 0, & x < a \end{cases}, - \infty < x < + \infty\end{split}\]

The cumulative distribution function is as follows:

\[\begin{split}F_{a, \beta}(x) = \begin{cases} 1 - \exp (-\frac{(x-a)}{\beta}), & x \geq a \\ 0, & x < a \end{cases}, - \infty < x < + \infty\end{split}\]

API

Syntax

template<typename RealType, typename Method>
class exponential {
public:
  using method_type = Method;
  using result_type = RealType;

  exponential(): exponential((RealType)0.0, (RealType)1.0){}
  explicit exponential(RealType mean, RealType stddev);
  explicit exponential(const param_type& pt);

  RealType a() const;
  RealType beta() const;
  param_type param() const;
  void param(const param_type& pt);
};

Include Files

  • oneapi/mkl/rng/device.hpp

Template Parameters

typename RealType

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

float

double

typename Method

Generation method. The specific values are as follows:

oneapi::mkl::rng::device::exponential_method::icdf

oneapi::mkl::rng::device::exponential_method::icdf_accurate

See brief descriptions of the methods in Distributions Template Parameter Method

Note: To enable extra optimizations based on Vector Math functions, define the MKL_RNG_USE_BINARY_CODE macro and link static oneMKL libraries according to the output produced by Intel® oneAPI Math Kernel Library Link Line Advisor. It may improve performance on some hardware.

Input Parameters

Name

Type

Description

a

RealType (float, double)

Displacement a.

beta

RealType (float, double)

Scalefactor \(\beta\).