Package: wrswoR 1.2.1.9018

wrswoR: Weighted Random Sampling without Replacement

A collection of implementations of classical and novel algorithms for weighted sampling without replacement.

Authors:Kirill Müller [aut, cre]

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wrswoR_1.2.1.9018.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
wrswoR/json (API)

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

Bug tracker:https://github.com/krlmlr/wrswor/issues

Pkgdown/docs site:https://krlmlr.github.io

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

On CRAN:

Conda:

cpp

7.92 score 20 stars 4 packages 46 scripts 2.0k downloads 8 exports 1 dependencies

Last updated from:913b605137. Checks:15 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-arm64OK159
linux-devel-x86_64OK191
source / vignettesOK178
linux-release-arm64OK152
linux-release-x86_64OK169
macos-release-arm64OK98
macos-release-x86_64OK202
macos-oldrel-arm64OK85
macos-oldrel-x86_64OK298
windows-devel-arm64OK215
windows-devel-x86_64OK190
windows-release-arm64OK222
windows-release-x86_64OK112
windows-oldrel-x86_64OK112
wasm-releaseOK121

Exports:sample_int_cccranksample_int_ccranksample_int_cranksample_int_expjsample_int_expjssample_int_Rsample_int_ranksample_int_rej

Dependencies:Rcpp

Readme and manuals

Help Manual

Help pageTopics
Faster weighted sampling without replacementwrswoR-package wrswoR
Weighted sampling without replacementsample_int sample_int_cccrank sample_int_ccrank sample_int_crank sample_int_expj sample_int_expjs sample_int_R sample_int_rank sample_int_rej