Estimating Finite State Machine Models from Data
Extracts slot of action_vec
Add interaction numbers for panel data
Extracts performance
Builds Bitstring
Compares FSMs
datafsm: A package for estimating FSM models.
Decodes Action Vector
Decodes State Matrix
Determines if State Matrix is Degenerate for Given Data Set.
Extracts slot relevant to estimating the fsm
Use a Genetic Algorithm to Estimate a Finite-state Machine Model
Estimate Optimal Number of States of a Finite-state Machine Model
Use a Genetic Algorithm to Estimate a Finite-state Machine Model n-tim...
Find Indices for Non-identifiable Elements of State Matrix.
Fitness Function in C++
An S4 class to return the results of using a GA to estimate a FSM with...
Measure Model Performance
Extracts number of states
Variable Importance Measure for A FSM Model
Extracts slot of variable importances
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.
Useful links