LedgerInvesting/bayesblend

Easily combine predictions from multiple Bayesian models using techniques including (pseudo) Bayesian model averaging, hierarchical stacking, and more!

BayesBlend

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.

Citing

If you use BayesBlend, we would appreciate it if you cite our writeup!

BibTex

@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}
}

MLA

Haines, Nathaniel and Conor Goold. “BayesBlend: Easy Model Blending using Pseudo-Bayesian Model Averaging, Stacking and Hierarchical Stacking in Python.” arXiv (2024): 2405.00158.

APA

Haines, N., & Goold, C. (2024). BayesBlend: Easy Model Blending using Pseudo-Bayesian Model Averaging, Stacking and Hierarchical Stacking in Python. arXiv, 2405.00158.

Chicago

Haines, Nathaniel and Conor Goold. “BayesBlend: Easy Model Blending using Pseudo-Bayesian Model Averaging, Stacking and Hierarchical Stacking in Python.” arXiv (2024): 2405.00158.