Package: zigg 0.0.0

zigg: Lightweight Interfaces to the 'Ziggurat' Pseudo Random Number Generator

'Ziggurat', originally 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 pseudo-random number generator (or '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(++) 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 older package 'RcppZiggurat' which offers a comparisone among multiple alternative implementations. These 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 so if in doubt use of the base R function generatrs remains the general recommendation.

Authors:Dirk Eddelbuettel [aut, cre]

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zigg.pdf |zigg.html
zigg/json (API)

# Install 'zigg' in R:
install.packages('zigg', repos = c('https://eddelbuettel.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/eddelbuettel/zigg/issues

Uses libs:
  • c++– GNU Standard C++ Library v3

On CRAN:

cpp

2.48 score 3 stars 4 scripts 4 exports 0 dependencies

Last updated 3 days agofrom:34cbe8ed46. Checks:9 OK. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKJan 12 2025
R-4.5-win-x86_64OKJan 12 2025
R-4.5-linux-x86_64OKJan 12 2025
R-4.4-win-x86_64OKJan 12 2025
R-4.4-mac-x86_64OKJan 12 2025
R-4.4-mac-aarch64OKJan 12 2025
R-4.3-win-x86_64OKJan 12 2025
R-4.3-mac-x86_64OKJan 12 2025
R-4.3-mac-aarch64OKJan 12 2025

Exports:zrexpzrnormzrunifzsetseed

Dependencies: