Supporting Bayesian modeling workflows with iterative filtering for multiverse analysis

Statistical Modeling, Causal Inference, and Social Science 2024-10-21

Summary:

Anna Riha, Nikolas Siccha, Antti Oulasvirta, and Aki Vehtari write: When building statistical models for Bayesian data analysis tasks, required and optional iterative adjustments and different modelling choices can give rise to numerous candidate models. In particular, checks and evaluations … Continue reading

Link:

https://statmodeling.stat.columbia.edu/2024/10/21/supporting-bayesian/

From feeds:

Statistics and Visualization » Statistical Modeling, Causal Inference, and Social Science

Tags:

bayesian

Authors:

Andrew

Date tagged:

10/21/2024, 12:04

Date published:

10/21/2024, 09:16