rlssm is a Python package for fitting reinforcement learning (RL) models, sequential sampling models (DDM, RDM, LBA, ALBA, and ARDM), and combinations of the two, using Bayesian parameter estimation.
Parameter estimation is done at an individual or hierarchical level using PyStan, the Python Interface to Stan. Stan performs Bayesian inference using the No-U-Turn sampler, a variant of Hamiltonian Monte Carlo.
You can install the rlssm package using:
pip install rlssm
Make sure you have the dependecies installed first.
- pystan=2.19
- pandas
- scipy
- seaborn
If you have Andaconda or miniconda installed and you would like to create a separate environment:
conda create --n stanenv python=3 pandas scipy seaborn pystan=2.19
conda activate stanenv
pip install rlssm
The latest documentation can be found here: https://rlssm.readthedocs.io/
