econirl
  • Overview
  • Quick Start
  • Loading Data and Pre-Estimation
  • Core Estimators
    • NFXP
    • CCP
    • TD-CCP
    • MCE-IRL
    • Neural MCE-IRL
    • AIRL
    • AIRL-Het
    • GLADIUS
  • Other Estimators
    • NNES
    • MPEC
    • UFXP
    • RHIP
    • f-IRL
    • IQ-Learn
  • Choosing and Comparing Estimators
  • Post-Estimation Diagnostics
  • Theory
    • Soft Bellman and DDC-MaxEnt Equivalence
    • Identification and Anchors
    • Classical DDC Proof Routes
    • IRL Identification Boundaries
    • GLADIUS and ERM
    • Reward Projection and Feature Rank
  • Replications
  • Simulation Studies
    • Bus engine replacement
    • Gridworld navigation
    • Route choice on a synthetic road network
    • Consumer stockpiling of a storable good
    • Fleet maintenance (multi-component bus engine replacement)
    • Content consumption with latent viewer types
    • RHIP recovers the demonstrator’s planning horizon
  • API References
    • econirl.DDCProblem
    • econirl.Panel
    • econirl.Trajectory
    • econirl.TrajectoryPanel
    • econirl.RewardSpec
    • econirl.SufficientStats
    • econirl.NFXP
    • econirl.CCP
    • econirl.TDCCP
    • econirl.UFXP
    • econirl.NNES
    • econirl.SEES
    • econirl.MaxEntIRL
    • econirl.MaxMarginIRL
    • econirl.MCEIRL
    • econirl.MCEIRLNeural
    • econirl.IQLearn
    • econirl.GLADIUS
    • econirl.AIRL
    • econirl.NeuralUFXP
    • econirl.RustBusEnvironment
    • econirl.environments.ArrayMDP
    • econirl.environments.random_mdp
    • econirl.simulation.simulate_panel
    • econirl.Utility
    • econirl.LinearCost
    • econirl.make_utility
    • econirl.TransitionEstimator
    • econirl.preprocessing.check_panel_structure
    • econirl.preprocessing.feature_diagnostics
    • econirl.datasets
  • References
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