doRNG: Generic Reproducible Parallel Backend for 'foreach' Loops

Provides functions to perform reproducible parallel foreach loops, using independent random streams as generated by L'Ecuyer's combined multiple-recursive generator [L'Ecuyer (1999), <doi:10.1287/opre.47.1.159>]. It enables to easily convert standard %dopar% loops into fully reproducible loops, independently of the number of workers, the task scheduling strategy, or the chosen parallel environment and associated foreach backend.

Version: 1.7.1
Depends: R (≥ 3.0.0), foreach, rngtools (≥ 1.3)
Imports: stats, utils, iterators, pkgmaker (≥ 0.20)
Suggests: doParallel, doMPI, doRedis, rbenchmark, devtools, knitr, bibtex, testthat
Published: 2018-06-22
Author: Renaud Gaujoux [aut, cre]
Maintainer: Renaud Gaujoux <renozao at protonmail.com>
BugReports: http://github.com/renozao/doRNG/issues
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
URL: https://renozao.github.io/doRNG
NeedsCompilation: no
Materials: NEWS
In views: HighPerformanceComputing
CRAN checks: doRNG results

Downloads:

Reference manual: doRNG.pdf
Vignettes: Using the package doRNG
Package source: doRNG_1.7.1.tar.gz
Windows binaries: r-devel: doRNG_1.7.1.zip, r-release: doRNG_1.7.1.zip, r-oldrel: doRNG_1.7.1.zip
OS X binaries: r-release: doRNG_1.7.1.tgz, r-oldrel: doRNG_1.7.1.tgz
Old sources: doRNG archive

Reverse dependencies:

Reverse depends: SparseMDC
Reverse imports: bdots, bestNormalize, blockmodeling, condSURV, Counterfactual, CovSelHigh, fabMix, fuzzyforest, gbts, groupedSurv, Mediana, momentuHMM, mplot, RSNPset, SGP, skpr, survidm, telefit, WebGestaltR
Reverse suggests: CPAT, cutpointr, doFuture, GA, GAparsimony, inlmisc, ptycho, SimRVPedigree

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