Posts by Ricardo Vieira
Hidden Markov Models in PyMC: marginalize and recover a DiscreteMarkovChain
- 18 July 2026
A hidden Markov model (HMM) describes a system that moves through a sequence of hidden discrete states, where each state emits a noisy observation. We never see the states directly; we only see the emissions, and we want to reason backward to the states that most likely produced them.
Fitting a Reinforcement Learning Model to Behavioral Data with PyMC
- 05 August 2022
Reinforcement Learning models are commonly used in behavioral research to model how animals and humans learn, in situtions where they get to make repeated choices that are followed by some form of feedback, such as a reward or a punishment.
How to wrap a JAX function for use in PyMC
- 24 March 2022
This notebook uses libraries that are not PyMC dependencies and therefore need to be installed specifically to run this notebook. Open the dropdown below for extra guidance.
Using a “black box” likelihood function
- 16 December 2021
There is a related example that discusses how to use a likelihood implemented in JAX