| Title: | Parallel Pseudo Random Number Generator (PPRNG) 'sitmo' HeaderFiles |
| Version: | 2.0.2 |
| Description: | Provided within are two high quality and fast PPRNGs that may be used in an 'OpenMP' parallel environment. In addition, there is a generator for one dimensional low-discrepancy sequence. The objective of this library to consolidate the distribution of the 'sitmo' (C++98 & C++11), 'threefry' and 'vandercorput' (C++11-only) engines on CRAN by enabling others to link to the header files inside of 'sitmo' instead of including a copy of each engine within their individual package. Lastly, the package contains example implementations using the 'sitmo' package and three accompanying vignette that provide additional information. |
| Depends: | R (≥ 3.2.0) |
| URL: | https://github.com/coatless/sitmo,http://thecoatlessprofessor.com/projects/sitmo/,https://github.com/stdfin/random/ |
| BugReports: | https://github.com/coatless/sitmo/issues |
| License: | MIT + file LICENSE |
| LinkingTo: | Rcpp |
| Imports: | Rcpp (≥ 0.12.13) |
| RoxygenNote: | 7.1.1 |
| Suggests: | knitr, rmarkdown, ggplot2 |
| VignetteBuilder: | knitr |
| Encoding: | UTF-8 |
| NeedsCompilation: | yes |
| Packaged: | 2021-10-13 03:57:03 UTC; ronin |
| Author: | James Balamuta [aut, cre, cph], Thijs van den Berg [aut, cph], Ralf Stubner [ctb] |
| Maintainer: | James Balamuta <balamut2@illinois.edu> |
| Repository: | CRAN |
| Date/Publication: | 2021-10-13 04:50:02 UTC |
sitmo: Parallel Pseudo Random Number Generator (PPRNG) 'sitmo' Header Files
Description
Provided within are two high quality and fast PPRNGs that may beused in an 'OpenMP' parallel environment. In addition, there is a generatorfor one dimensional low-discrepancy sequence. The objective of this libraryto consolidate the distribution of the 'sitmo' (C++98 & C++11), 'threefry' and'vandercorput' (C++11-only) engines on CRAN by enabling others to link to theheader files inside of 'sitmo' instead of including a copy of each enginewithin their individual package. Lastly, the package contains exampleimplementations using the 'sitmo' package and three accompanying vignette thatprovide additional information.
Author(s)
Maintainer: James Balamutabalamut2@illinois.edu (ORCID) [copyright holder]
Authors:
Thijs van den Bergthijs@sitmo.com [copyright holder]
Other contributors:
Ralf Stubnerralf.stubner@daqana.com [contributor]
See Also
Useful links:
Report bugs athttps://github.com/coatless/sitmo/issues
Random Uniform Number Generator using base R
Description
The function provides an alternative implementation of random uniform distributionsampling using R's rng scope.
Usage
runif_r(n, min = 0, max = 1)Arguments
n | An |
min | A |
max | A |
Examples
set.seed(134)b = runif_r(10)Random Uniform Number Generator with sitmo
Description
The function provides an implementation of sampling from a random uniform distribution
Usage
runif_sitmo(n, min = 0, max = 1, seed = 1L)Arguments
n | An |
min | A |
max | A |
seed | A special |
Value
Anumeric vector containing the realizations.
Examples
a = runif_sitmo(10)Example RNG Draws with sitmo
Description
Shows a basic setup and use case for sitmo.
Usage
sitmo_draws(n)Arguments
n | A |
Value
Avec with random sequences.
Examples
n = 10a = sitmo_draws(n)Example Seed Set and RNG Draws with sitmo
Description
Shows how to set a seed in sitmo.
Usage
sitmo_engine_reset(n, seed)Arguments
n | An |
seed | An |
Value
Amatrix with random sequences.
Examples
n = 10a = sitmo_engine_reset(n, 1337)isTRUE(all.equal(a[,1],a[,2]))Example Seed Set and RNG Draws with sitmo
Description
Shows how to set a seed in sitmo.
Usage
sitmo_engine_seed(n, seed)Arguments
n | An |
seed | An |
Value
Avector with random sequences.
Examples
n = 10a = sitmo_engine_seed(n, 1337)b = sitmo_engine_seed(n, 1337)c = sitmo_engine_seed(n, 1338)isTRUE(all.equal(a,b))isTRUE(all.equal(a,c))Test Generation using sitmo and C++11
Description
The function provides an implementation of creating realizations from the default engine.
Usage
sitmo_parallel(n, seeds)Arguments
n | An |
seeds | A |
Details
The following function's true power is only accessible on platforms that support OpenMP (e.g. Windows and Linux).However, it does provide a very good example as to how to make ones code applicable across multiple platforms.
With this being said, how we determine how many cores to split the generation to is governed by the number of seeds supplied.In the event that one is using OS X, only the first seed supplied is used.
Value
Avec containing the realizations.
Examples
a = sitmo_parallel(10, c(1))b = sitmo_parallel(10, c(1,2))c = sitmo_parallel(10, c(1,2))# True on only OS X or systems without openmpisTRUE(all.equal(a,b))isTRUE(all.equal(b,c))Two RNG engines running side-by-side
Description
Shows how to create two separate RNGs and increase them together.
Usage
sitmo_two_seeds(n, seeds)Arguments
n | An |
seeds | A |
Value
Amatrix with random sequences.
Examples
n = 10a = sitmo_two_seeds(n, c(1337, 1338))b = sitmo_two_seeds(n, c(1337, 1337))isTRUE(all.equal(a[,1], a[,2]))isTRUE(all.equal(b[,1], b[,2]))isTRUE(all.equal(a[,1], b[,1]))