wrswoR: Weighted Random Sampling without Replacement

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

Version: 1.1.1
Depends: R (≥ 3.0.2)
Imports: logging (≥ 0.4-13), Rcpp
LinkingTo: Rcpp (≥ 0.11.5)
Suggests: BatchExperiments, BiocManager, dplyr, ggplot2, import, kimisc (≥ 0.2-4), knitcitations, knitr, metap, microbenchmark, rmarkdown, roxygen2, rticles (≥ 0.1), sampling, testthat, tidyr, tikzDevice (≥ 0.9-1)
Published: 2020-07-26
DOI: 10.32614/CRAN.package.wrswoR
Author: Kirill Müller [aut, cre]
Maintainer: Kirill Müller <krlmlr+r at mailbox.org>
BugReports: https://github.com/krlmlr/wrswoR/issues
License: GPL-3
URL: http://krlmlr.github.io/wrswoR
NeedsCompilation: yes
Materials: README NEWS
CRAN checks: wrswoR results


Reference manual: wrswoR.pdf


Package source: wrswoR_1.1.1.tar.gz
Windows binaries: r-devel: wrswoR_1.1.1.zip, r-release: wrswoR_1.1.1.zip, r-oldrel: wrswoR_1.1.1.zip
macOS binaries: r-release (arm64): wrswoR_1.1.1.tgz, r-oldrel (arm64): wrswoR_1.1.1.tgz, r-release (x86_64): wrswoR_1.1.1.tgz, r-oldrel (x86_64): wrswoR_1.1.1.tgz
Old sources: wrswoR archive

Reverse dependencies:

Reverse imports: MEB, mlfit, rakeR, simPop
Reverse suggests: mvgam, singleCellHaystack


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