Package: wrswoR 1.2.1.9002

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]

wrswoR_1.2.1.9002.tar.gz
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wrswoR_1.2.1.9002.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
wrswoR/json (API)
NEWS

# 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

7.83 score 20 stars 4 packages 30 scripts 4.8k downloads 8 exports 1 dependencies

Last updated from:a74333b87c. Checks:13 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-arm64OK132
linux-devel-x86_64OK150
source / vignettesOK258
linux-release-arm64OK143
linux-release-x86_64OK151
macos-release-arm64OK91
macos-release-x86_64OK232
macos-oldrel-arm64OK70
macos-oldrel-x86_64OK197
windows-develOK105
windows-releaseOK98
windows-oldrelOK90
wasm-releaseOK131

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