Hierarchical Bayesian Modeling

Bayesian Modeling
Statistics
Package
R
STAN
Python
Author

David Munoz Tord

Published

March 8, 2021

Hierarchical Bayesian modeling of Decision-Making tasks

I collaborated on the Hierarchical Bayesian modeling of Decision-Making tasks library hBayesDM, a user-friendly package that offers hierarchical Bayesian analysis of various computational models on an array of decision-making tasks.

simulation

It uses STAN for Bayesian inference and supports both {R} and {Python}. hBayesDM’s goal is to help interpreting experimental data through computational models using a full Bayesian statistical inference approach with MCMC sampling. My work involved the implementation of the Q-learning algorithm for reinforcement learning tasks.

RL

Check out the project on GitHub.