rpgm.rnorm: Fast Simulation of Normal Random Variables

In rpgm: Fast Simulation of Normal/Exponential Random Variables and Stochastic Differential Equations / Poisson Processes

Description

The function rpgm.rnorm uses the Ziggurat algorithm with a 128-regions table, in order to simulate normal random variables faster than rnorm.

Usage

rpgm.rnorm(n, mean = 0, sd = 1, nthreads = 1L)

Arguments

n	integer, number of simulations.
mean	double, the mean (or the vector of means).
sd	double, the standard deviation (or the vector of standard deviations).
nthreads	integer, the number of threads to use for parallelism.

Details

If mean or sd are not specified they assume the default values of 0 and 1, respectively. By default the number of threads is 1 so there is no multi-core.

Value

A vector of i.i.d. normal random variables.

Note

For a big number of simulations, with nthreads = 1, it is approximately four times faster than the usual rnorm. For one simulution, it is around one half faster.

Author(s)

Nicolas Baradel - PGM Solutions

References

https://en.wikipedia.org/wiki/Ziggurat_algorithm

See Also

http://pgm-solutions.com/packages

Examples

rpgm.rnorm(5)
rpgm.rnorm(5, nthreads = maxthreads())

rpgm documentation built on March 18, 2018, 2:24 p.m.