paramsim: Parameterized Simulation (original) (raw)
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 |
| License: | GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
| NeedsCompilation: | no |
| CRAN checks: | paramsim results |
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