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The implementation is influenced by our\npackage 'RcppZiggurat' which offers a comparison among multiple\nalternative implementations but presented here in a\nlighter-weight implementation that is easier to use by other\npackages. The PRNGs provided are generally faster than the ones\nin base R: on our machine, the relative gains for normal,\nexponential and uniform are on the order of 7.4, 5.2 and 4.7\ntimes faster than base R. However, these generators are of\npotentially lesser quality and shorter period so if in doubt\nuse of the base R functions remains the general recommendation.", "URL": "https://github.com/eddelbuettel/zigg", "BugReports": "https://github.com/eddelbuettel/zigg/issues", "License": "GPL (>= 2)", "Encoding": "UTF-8", "RoxygenNote": "6.0.1", "Repository": "https://eddelbuettel.r-universe.dev", "Date/Publication": "2026-10-15 17:10:11 UTC", "RemoteUrl": "https://github.com/eddelbuettel/zigg", "RemoteRef": "HEAD", "RemoteSha": "2c9b7578156cbc2434d88411869c36f23b5ee49b", "NeedsCompilation": "yes", "Packaged": { "Date": "2026-10-15 17:17:05 UTC", "User": "root" }, "Author": "Dirk Eddelbuettel [aut, cre] (ORCID:\n)", "Maintainer": "Dirk Eddelbuettel ", "_user": "eddelbuettel", "_type": "src", "_file": "zigg_0.0.2.tar.gz", "_fileid": "https://r2.ropensci.org/a0ba9266d091402a6ddb66483df88d4f557d4f3177871dfb2fb8edd50b7affca", "_filesize": 106226, "_sha256": 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