Suggests: censReg, cluster, clustMixType, CPE, dbscan, e1071, ggpubr,
Hmisc, igraph, mclust, parallel, RColorBrewer, reshape2,
Packaged: 2021-10-17 11:54:56 UTC; lfaucheux

Title: Foreach parallel adaptor for the Rmpi package

Suggests: multicore(>= 0.1-3), nws(>= 1.7.0.0), randomForest

Title: Foreach Parallel Adaptor for the Rmpi Package
Authors@R: person("Steve", "Weston", role=c("cre", "aut", "cph"),

Title: Foreach parallel adaptor for the parallel package

Title: Foreach Parallel Adaptor for the 'parallel' Package

Packaged: 2022-01-16 17:54:13 UTC; folashade

Author: Revolution Analytics, Steve Weston

Title: Generic Reproducible Parallel Backend for foreach Loops
Description: This package provides functions to perform reproducible
parallel foreach loops, using independent random streams as
generated by the package rstream. 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
Depends: R (>= 2.13), methods, stats, foreach, rstream (>= 1.3.1)

Description: This package 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.
Depends: R (>= 2.14), methods, stats, foreach, parallel

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.
Suggests: doParallel, doMPI, knitr, bibtex

Suggests: doParallel, doMPI, doRedis, knitr, bibtex, rbenchmark

Depends: R (>= 2.14), methods, stats, foreach, parallel, iterators