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), ]. 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.

Documentation

Manual: doRNG.pdf
Vignettes:

Maintainer: Renaud Gaujoux <renaud at tx.technion.ac.il>

Author(s): Renaud Gaujoux

Install package and any missing dependencies by running this line in your R console:

install.packages("doRNG")

Depends R (>= 3.0.0), foreach, rngtools(>=1.2.4)
Imports stats, utils, iterators, pkgmaker(>=0.20)
Suggests doParallel, doMPI, doRedis, rbenchmark, RUnit, devtools, knitr, bibtex
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bdots, condSURV, Counterfactual, CovSelHigh, fuzzyforest, gbts, Mediana, RSNPset, SGP, survidm
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darch, doFuture, GA, ptycho
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Package doRNG
Materials
URL https://renozao.github.io/doRNG
Task Views HighPerformanceComputing
Version 1.6.6
Published 2017-04-10
License GPL (>= 2)
BugReports http://github.com/renozao/doRNG/issues
SystemRequirements
NeedsCompilation no
Citation
CRAN checks doRNG check results
Package source doRNG_1.6.6.tar.gz