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 gmail.com>
License:	GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation:	no
CRAN checks:	paramsim results

Documentation:

Reference manual:	paramsim.pdf
Vignettes:	paramsim

Downloads:

Package source:	paramsim_0.1.0.tar.gz
Windows binaries:	r-devel: paramsim_0.1.0.zip, r-release: paramsim_0.1.0.zip, r-oldrel: paramsim_0.1.0.zip
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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