datafsm: Estimating Finite State Machine Models from Data

Automatic generation of finite state machine models of dynamic decision-making that both have strong predictive power and are interpretable in human terms. We use an efficient model representation and a genetic algorithm-based estimation process to generate simple deterministic approximations that explain most of the structure of complex stochastic processes. We have applied the software to empirical data, and demonstrated it's ability to recover known data-generating processes by simulating data with agent-based models and correctly deriving the underlying decision models for multiple agent models and degrees of stochasticity.

Version:	0.2.4
Depends:	R (≥ 4.0), methods (≥ 4.0), stats (≥ 4.0)
Imports:	caret (≥ 6.0), GA (≥ 3.2), Rcpp (≥ 1.0)
LinkingTo:	Rcpp (≥ 1.0)
Suggests:	doParallel (≥ 1.0), foreach (≥ 1.5), testthat (≥ 3.0), diagram (≥ 1.6), knitr (≥ 1.33), rmarkdown (≥ 2.8), pander (≥ 0.6), dplyr (≥ 1.0), tidyr (≥ 1.0), purrr (≥ 0.3)
Published:	2021-05-29
DOI:	10.32614/CRAN.package.datafsm
Author:	John J. Nay [aut], Jonathan M. Gilligan [cre, aut]
Maintainer:	Jonathan M. Gilligan <jonathan.gilligan at vanderbilt.edu>
BugReports:	https://github.com/jonathan-g/datafsm/issues
License:	MIT + file LICENSE
URL:	https://jonathan-g.github.io/datafsm/, https://github.com/jonathan-g/datafsm
NeedsCompilation:	yes
Language:	en-US
Citation:	datafsm citation info
Materials:	NEWS
CRAN checks:	datafsm results

Documentation:

Reference manual:	datafsm.pdf
Vignettes:	Introduction to datafsm Example with real data

Downloads:

Package source:	datafsm_0.2.4.tar.gz
Windows binaries:	r-devel: datafsm_0.2.4.zip, r-release: datafsm_0.2.4.zip, r-oldrel: datafsm_0.2.4.zip
macOS binaries:	r-release (arm64): datafsm_0.2.4.tgz, r-oldrel (arm64): datafsm_0.2.4.tgz, r-release (x86_64): datafsm_0.2.4.tgz, r-oldrel (x86_64): datafsm_0.2.4.tgz
Old sources:	datafsm archive

Linking:

Please use the canonical form https://CRAN.R-project.org/package=datafsm to link to this page.