RcppZiggurat-package: Collection and comparison of different Ziggurat RNGs

In RcppZiggurat: 'Rcpp' Integration of Different "Ziggurat" Normal RNG Implementations

Description

Marsaglia and Tsang (JSS, 2000) introduced a very fast random number generator for drawing from a standard normal distribution. Leong, Zhang, Lee, Luk and Villasenor (JSS, 2005) suggested a simple improvement to provide better distributional properties.

This package implements both approaches, both in simple forms faithful to original papers, as well as in extended and modified versions of the C/C++ code provided by John Burkardt.

It also includes a variant which calls the fairly widely used Ziggurat implementation by Jochen Voss that is part of the GNU GSL. It uses the Mersenne-Twister as its uniform generator and does not suffer from the problem identified by Leong et al.

Author(s)

Dirk Eddelbuettel

References

George Marsaglia and Wai Wan Tsang. The Ziggurat Method for Generating Random Variables. Journal of Statistical Software, Vol 5, Iss 8, Oct 2000 https://www.jstatsoft.org/v05/i08

Philip H W Leong, Ganglie Zhang, Dong-U Lee, Wayne Luk, and John Villasenor. A Comment on the Implementation of the Ziggurat method, Journal of Statistical Software, Vol 12, Iss 7, Feb 2005 https://www.jstatsoft.org/v12/i07

Website of John Burkardt. https://people.sc.fsu.edu/~jburkardt/

Website of Jochen Voss. https://www.seehuhn.de/pages/ziggurat

Examples

  set.seed(42)
  system.time(replicate(500, rnorm(10000)))

  zsetseed(42)
  system.time(replicate(500, zrnorm(10000)))

Example output

   user  system elapsed 
  0.807   0.063   0.873 
   user  system elapsed 
  0.249   0.082   0.338 

RcppZiggurat documentation built on Oct. 23, 2020, 8:09 p.m.