datafsm: Estimating Finite State Machine Models from Data

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.

AuthorNay John J. [cre, aut], Gilligan Jonathan M. [aut]
Date of publication2015-09-08 00:25:33
MaintainerNay John J. <john.j.nay@gmail.com>
LicenseMIT + file LICENSE
Version0.1.0
http://johnnay.github.io/datafsm/

View on CRAN

Functions

action_vec Man page
action_vec Man page
action_vec,ga_fsm-method Man page
action_vec,ga_fsm-method Man page
barplot,ga_fsm-method Man page
barplot,ga_fsm-method Man page
best_performance Man page
best_performance Man page
best_performance,ga_fsm-method Man page
best_performance,ga_fsm-method Man page
build_bitstring Man page
build_bitstring Man page
compare_fsm Man page
compare_fsm Man page
datafsm Man page
datafsm Man page
datafsm-package Man page
datafsm-package Man page
decode_action_vec Man page
decode_action_vec Man page
decode_state_mat Man page
decode_state_mat Man page
degeneracy_check Man page
degeneracy_check Man page
dotchart,ga_fsm-method Man page
dotchart,ga_fsm-method Man page
estimation_details Man page
estimation_details Man page
estimation_details,ga_fsm-method Man page
estimation_details,ga_fsm-method Man page
evolve_model Man page
evolve_model Man page
evolve_model_cv Man page
evolve_model_cv Man page
find_wildcards Man page
find_wildcards Man page
fitnessCPP Man page
fitnessCPP Man page
ga_fsm-class Man page
ga_fsm-class Man page
plot,ga_fsm,ANY-method Man page
plot,ga_fsm,ANY-method Man page
plot,ga_fsm-method Man page
plot,ga_fsm-method Man page
predict,ga_fsm-method Man page
predict,ga_fsm-method Man page
print,ga_fsm-method Man page
print,ga_fsm-method Man page
show,ga_fsm-method Man page
show,ga_fsm-method Man page
states Man page
states Man page
states,ga_fsm-method Man page
states,ga_fsm-method Man page
summary,ga_fsm-method Man page
summary,ga_fsm-method Man page
var_imp Man page
var_imp Man page
varImp Man page
varImp Man page
varImp,ga_fsm-method Man page
varImp,ga_fsm-method Man page

Files

datafsm
datafsm/inst
datafsm/inst/CITATION
datafsm/inst/doc
datafsm/inst/doc/datafsmVignette.html
datafsm/inst/doc/datafsmVignette.R
datafsm/inst/doc/datafsmVignette.Rmd
datafsm/tests
datafsm/tests/testthat.R
datafsm/tests/testthat
datafsm/tests/testthat/test_mainfunc.R
datafsm/tests/testthat/test_varImp.R
datafsm/src
datafsm/src/RcppExports.cpp
datafsm/src/fitnessCPP.cpp
datafsm/NAMESPACE
datafsm/R
datafsm/R/class_def.R
datafsm/R/compare_fsm.R
datafsm/R/var_imp.R
datafsm/R/evolve_model.R
datafsm/R/decode_action_vec.R
datafsm/R/evolve_model_cv.R
datafsm/R/datafsm.R
datafsm/R/build_bitstring.R
datafsm/R/RcppExports.R
datafsm/R/decode_state_mat.R
datafsm/R/degeneracy_check.R
datafsm/vignettes
datafsm/vignettes/datafsmVignette.Rmd
datafsm/MD5
datafsm/build
datafsm/build/vignette.rds
datafsm/DESCRIPTION
datafsm/man
datafsm/man/states.Rd datafsm/man/ga_fsm-class.Rd datafsm/man/find_wildcards.Rd datafsm/man/evolve_model.Rd datafsm/man/decode_action_vec.Rd datafsm/man/fitnessCPP.Rd datafsm/man/datafsm.Rd datafsm/man/degeneracy_check.Rd datafsm/man/decode_state_mat.Rd datafsm/man/action_vec.Rd datafsm/man/var_imp.Rd datafsm/man/evolve_model_cv.Rd datafsm/man/compare_fsm.Rd datafsm/man/best_performance.Rd datafsm/man/build_bitstring.Rd datafsm/man/varImp.Rd datafsm/man/estimation_details.Rd
datafsm/LICENSE

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All documentation is copyright its authors; we didn't write any of that.