simsalapar-package: Tools for Simulation Studies in Parallel with R

Description

Tools for setting up, conducting, and evaluating larger-scale simulation studies, including parallel computations, in R.

Marius Hofert and Martin Maechler <maechler@stat.math.ethz.ch>

Maintainer: Marius Hofert <marius.hofert@math.ethz.ch>

The DESCRIPTION file: tools:::Rd_package_DESCRIPTION("simsalapar") tools:::Rd_package_indices("simsalapar")

varlist(): creates a variable specification list.
dimnames2varlist(): creates a variable specification list from given dimension names.
getEl(): extracts elements from a variable list.
mkGrid(): function for creating a grid of all variables of type “grid”; see mkGrid().
mkNms(): builds a list of names from a variable list; see mkNms().
get.n.sim(): extracts “n.sim”; see get.n.sim().
get.nonGrids(): extracts all variables not of type “grid”; see get.nonGrids().

tryCatch.W.E(): catching and storing warnings and errors simultaneously; see tryCatch.W.E().
doCallWE(): innermost computation (return value of doOne()): returns value, error, warning, and run time; see doCallWE().
LEseeds(): create a list of advanced .Random.seed's for “L'Ecuyer-CMRG”; see LEseeds().
printInfo(): displays information about the sub-job just finished; see printInfo().
subjob(): computes one row of the virtual grid in a simulation; see subjob().
mkTimer(): creates a function to be passed to doCallWE() as timer; see mkTimer().
doLapply(): sequentially iterates over all subjobs via standard lapply().
doForeach(): iterates over all subjobs in parallel (via foreach(), package foreach).
doRmpi(): iterates over all subjobs in parallel (via Rmpi's mpi.apply()).
doMclapply(): iterates over all subjobs in parallel (via mclapply()).
doClusterApply(): iterates over all subjobs in parallel (via clusterApply()).

doRes.equal(): convenience wrapper for comparing two results of the do* lapply-like functions; see doRes.equal().
mkAL(): converts a list of named 5-lists to an array of lists; see mkAL().
saveSim(): (optionally) converts a result list to an array of lists using mkAL(); see saveSim().
maybeRead(): (optionally) reads the provided .rds; see maybeRead().
getArray(): gets an array of 4-lists and computes an array of values, errors, warnings, or run times; see getArray().
array2df(): conveniently converts an array to a data.frame.
toLatex():: an S3 method for varlist and ftable.
fftable(): essentially calls format.ftable() and adds attributes ncv and nrv to the return object.
tablines(): computes ingredients for converting a character matrix with attributes to a LaTeX table.
wrapLaTable(): wraps a table and tabular environment around the lines of the body of a LaTeX table.
mayplot():: a matrix-like plot for arrays up to rank 5, with grid and gridBase.

Publication: Marius Hofert, Martin Maechler (2016). Parallel and Other Simulations in R Made Easy: An End-to-End Study. Journal of Statistical Software, 69(4), 1--44. tools:::Rd_expr_doi("10.18637/jss.v069.i04")
Preprint (for simsalapar 1.0-0; including timing info):: Hofert, M. and Mächler, M. (2013). Parallel and other simulations in R made easy: An end-to-end study. https://arxiv.org/abs/1309.4402

if (FALSE)  
 demo(TGforecasts)

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