BayesBlend provides an easy-to-use interface to combine predictions from multiple Bayesian models using techniques including (pseudo) Bayesian model averaging, hierarchical stacking, and more!
Check out the documentation for:
- The Getting Started guide on using BayesBlend.
- Our overview of Bayesian model averaging, stacking, hierarchical stacking and blending.
- How BayesBlend integrates with Arviz.
- How to contribute to BayesBlend.
If you use BayesBlend, we would appreciate it if you cite our writeup!
@misc{haines2024bayesblend,
title={BayesBlend: Easy Model Blending using Pseudo-Bayesian Model Averaging, Stacking and Hierarchical Stacking in Python},
author={Nathaniel Haines and Conor Goold},
year={2024},
eprint={2405.00158},
archivePrefix={arXiv},
primaryClass={stat.ME}
}
Haines, Nathaniel and Conor Goold. “BayesBlend: Easy Model Blending using Pseudo-Bayesian Model Averaging, Stacking and Hierarchical Stacking in Python.” arXiv (2024): 2405.00158.
Haines, N., & Goold, C. (2024). BayesBlend: Easy Model Blending using Pseudo-Bayesian Model Averaging, Stacking and Hierarchical Stacking in Python. arXiv, 2405.00158.
Haines, Nathaniel and Conor Goold. “BayesBlend: Easy Model Blending using Pseudo-Bayesian Model Averaging, Stacking and Hierarchical Stacking in Python.” arXiv (2024): 2405.00158.