Package: wrswoR 1.1.1.9011

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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NEWS

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

Peer review:

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

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

On CRAN:

6.61 score 18 stars 4 packages 27 scripts 734 downloads 7 exports 2 dependencies

Last updated 1 days agofrom:a988372ffd. Checks:OK: 9. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 22 2024
R-4.5-win-x86_64OKNov 22 2024
R-4.5-linux-x86_64OKNov 22 2024
R-4.4-win-x86_64OKNov 22 2024
R-4.4-mac-x86_64OKNov 22 2024
R-4.4-mac-aarch64OKNov 22 2024
R-4.3-win-x86_64OKNov 22 2024
R-4.3-mac-x86_64OKNov 22 2024
R-4.3-mac-aarch64OKNov 22 2024

Exports:sample_int_ccranksample_int_cranksample_int_expjsample_int_expjssample_int_Rsample_int_ranksample_int_rej

Dependencies:loggingRcpp

Readme and manuals

Help Manual

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