paramsim: Parameterized Simulation

This function obtains a Random Number Generator (RNG) or collection of RNGs that replicate the required parameter(s) of a distribution for a time series of data. Consider the case of reproducing a time series data set of size 20 that uses an autoregressive (AR) model with phi = 0.8 and standard deviation equal to 1. When one checks the arima.sin() function's estimated parameters, it's possible that after a single trial or a few more, one won't find the precise parameters. This enables one to look for the ideal RNG setting for a simulation that will accurately duplicate the desired parameters.

Version: 0.1.0
Depends: R (≥ 4.2.0)
Imports: forecast, foreach, parallel, doParallel, future, stats, tibble
Suggests: knitr, testthat (≥ 3.0.0)
Published: 2023-01-23
DOI: 10.32614/CRAN.package.paramsim
Author: Daniel James [cre, aut], Ayinde Kayode [aut]
Maintainer: Daniel James <futathesis at>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: no
CRAN checks: paramsim results


Reference manual: paramsim.pdf
Vignettes: paramsim


Package source: paramsim_0.1.0.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): paramsim_0.1.0.tgz, r-oldrel (arm64): paramsim_0.1.0.tgz, r-release (x86_64): paramsim_0.1.0.tgz, r-oldrel (x86_64): paramsim_0.1.0.tgz


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