Package: datafsm
Title: Estimating Finite State Machine Models from Data
Version: 0.2.0
Date: 2017-06-16
Authors@R: c( person("Nay", "John J.", 
      email = "john.j.nay@gmail.com", role = c("aut")), 
    person("Gilligan",  "Jonathan M.", 
      email = "jonathan.gilligan@vanderbilt.edu", role = c("cre", "aut")))
Description: Our method automatically generates 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.
URL: https://github.com/jonathan-g/datafsm
BugReports: https://github.com/jonathan-g/datafsm/issues
Depends: R (>= 3.1.1), methods, stats
License: MIT + file LICENSE
LazyData: true
LinkingTo: Rcpp
Suggests: doParallel, foreach, testthat, diagram, knitr
Imports: caret, GA, Rcpp
VignetteBuilder: knitr
RoxygenNote: 6.0.1
NeedsCompilation: yes
Packaged: 2017-06-17 02:14:05 UTC; Jonathan
Author: Nay John J. [aut],
  Gilligan Jonathan M. [cre, aut]
Maintainer: Gilligan Jonathan M. <jonathan.gilligan@vanderbilt.edu>
Repository: CRAN
Date/Publication: 2017-06-17 14:40:08 UTC
