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zigg  

Lightweight Interfaces to the 'Ziggurat' Pseudo Random Number Generator
View on CRAN: Click here


Download and install zigg package within the R console
Install from CRAN:
install.packages("zigg")

Install from Github:
library("remotes")
install_github("cran/zigg")

Install by package version:
library("remotes")
install_version("zigg", "0.0.2")



Attach the package and use:
library("zigg")
Maintained by
Dirk Eddelbuettel
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2025-01-31
Latest Update: 2025-01-31
Description:
The 'Ziggurat' pseudo-random number generator (or PRNG), introduced by Marsaglia and Tsang (2000, <doi:10.18637/jss.v005.i08>) and further improved by Leong et al (2005, <doi:10.18637/jss.v012.i07>), offers a lightweight and very fast PRNG for the normal, exponential, and uniform distributions. It is provided here in a small zero-dependency package. It can be used from R as well as from 'C/C++' code in other packages as is demonstrated by four included sample packages using four distinct methods to use the PRNG presented here in client package. The implementation is influenced by our package 'RcppZiggurat' which offers a comparison among multiple alternative implementations but presented here in a lighter-weight implementation that is easier to use by other packages. The PRNGs provided are generally faster than the ones in base R: on our machine, the relative gains for normal, exponential and uniform are on the order of 7.4, 5.2 and 4.7 times faster than base R. However, these generators are of potentially lesser quality and shorter period so if in doubt use of the base R functions remains the general recommendation.
How to cite:
Dirk Eddelbuettel (2025). zigg: Lightweight Interfaces to the 'Ziggurat' Pseudo Random Number Generator. R package version 0.0.2, https://cran.r-project.org/web/packages/zigg. Accessed 20 Feb. 2025.
Previous versions and publish date:
0.0.1 (2025-01-31 12:20)
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