clusterSetRNGSubStream

Sets the sub-stream RNG state within for Pierre L'Ecuyer's (1999)
algorithm. Should be used within distributed array jobs
after suitable L'Ecuyer's (1999) have been distributed to each array, and
each array is further defined to use multi-core processing. See
<code><a href="/link/clusterSetRNGStream?package=SimDesign&version=2.18" data-mini-rdoc="SimDesign::clusterSetRNGStream">clusterSetRNGStream</a></code> for further information.

Provides tools to safely and efficiently organize and execute
Monte Carlo simulation experiments in R.
The package controls the structure and back-end of Monte Carlo simulation experiments
by utilizing a generate-analyse-summarise workflow. The workflow safeguards against
common simulation coding issues, such as automatically re-simulating non-convergent results,
prevents inadvertently overwriting simulation files, catches error and warning messages
during execution, implicitly supports parallel processing with high-quality random number
generation, and provides tools for managing high-performance computing (HPC) array jobs
submitted to schedulers such as SLURM. For a pedagogical introduction to the package see
Sigal and Chalmers (2016) <doi:10.1080/10691898.2016.1246953>. For a more in-depth overview of
the package and its design philosophy see Chalmers and Adkins (2020) <doi:10.20982/tqmp.16.4.p248>.

Phil Chalmers

SimDesign

Structure for Organizing Monte Carlo Simulation Designs

Matthew Sigal

Ogreden Oguzhan

Mikko  Ronkko

clusterSetRNGSubStream function

<dl><dt>cl</dt>
<dd>A cluster from the <code>parallel</code> or <code>snow</code> package, or
(if <code>NULL</code>) the registered cluster</dd>
<dt>seed</dt>
<dd>An integer vector of length 7 as given by <code>.Random.seed</code> when
the L'Ecuyer-CMR RNG is in use. See<code><a href="/link/RNG?package=SimDesign&version=2.18" data-mini-rdoc="SimDesign::RNG">RNG</a></code> for the valid values</dd></dl>

Arguments

Sets the sub-stream RNG state within for Pierre L'Ecuyer's (1999)
algorithm. Should be used within distributed array jobs
after suitable L'Ecuyer's (1999) have been distributed to each array, and
each array is further defined to use multi-core processing. See
<code><a href='https://rdrr.io/r/parallel/RngStream.html'>clusterSetRNGStream</a></code> for further information.

Set RNG sub-stream for  Pierre L'Ecuyer's RngStreams — clusterSetRNGSubStream

<dl>

<dt>cl</dt>
<dd>A cluster from the <code>parallel</code> or <code>snow</code> package, or
(if <code>NULL</code>) the registered cluster</dd>


<dt>seed</dt>
<dd>An integer vector of length 7 as given by <code>.Random.seed</code> when
the L'Ecuyer-CMR RNG is in use. See<code><a href='https://rdrr.io/r/base/Random.html'>RNG</a></code> for the valid values</dd>

</dl>

clusterSetRNGSubStream: Set RNG sub-stream for Pierre L'Ecuyer's RngStreams

Description

Usage

Value

Arguments