Developer Reference

  • 2020.2
  • 07/15/2020
  • Public Content
Contents

Distribution Generators

oneMKL
VS
routines are used to generate random numbers with different types of distribution. Each function group is introduced below by the type of underlying distribution and contains a short description of its functionality, as well as specifications of the call sequence and the explanation of input and output parameters. Table
"Continuous Distribution Generators"
and Table
"Discrete Distribution Generators"
list the random number generator routines with data types and output distributions, and sets correspondence between data types of the generator routines and the basic random number generators.
Continuous Distribution Generators
Type of Distribution
Data Types
BRNG Data Type
Description
s
,
d
s
,
d
Uniform continuous distribution on the interval [
a,b
)
s
,
d
s
,
d
Normal (Gaussian) distribution
s
,
d
s
,
d
Multivariate normal (Gaussian) distribution
s
,
d
s
,
d
Exponential distribution
s
,
d
s
,
d
Laplace distribution (double exponential distribution)
s
,
d
s
,
d
Weibull distribution
s
,
d
s
,
d
Cauchy distribution
s
,
d
s
,
d
Rayleigh distribution
s
,
d
s
,
d
Lognormal distribution
s
,
d
s
,
d
Gumbel (extreme value) distribution
s
,
d
s
,
d
Gamma distribution
s
,
d
s
,
d
Beta distribution