484 citations · 849 across the 12 of their papers we have counts for
13 papers · 1 filter
Efficient estimation and correction of selection-induced bias with order statistics
Yann McLatchie, Aki Vehtari
Model selection aims to identify a sufficiently well performing model that is possibly simpler than the most complex model among a pool of candidates. However, the decision-making…
On Reparameterization Invariant Bayesian Point Estimates and Credible Regions
Aki Vehtari
This paper considers reparameterization invariant Bayesian point estimates and credible regions of model parameters for scientific inference and communication. The effect of intrin…
Bayesian hierarchical stacking: Some models are (somewhere) useful
Yuling Yao, Gregor Pirš, Aki Vehtari +1
Stacking is a widely used model averaging technique that asymptotically yields optimal predictions among linear averages. We show that stacking is most effective when model predict…
What are the most important statistical ideas of the past 50 years?
Andrew Gelman, Aki Vehtari
We review the most important statistical ideas of the past half century, which we categorize as: counterfactual causal inference, bootstrapping and simulation-based inference, over…
Bayesian Workflow
Andrew Gelman, Aki Vehtari, Daniel Simpson +7
The Bayesian approach to data analysis provides a powerful way to handle uncertainty in all observations, model parameters, and model structure using probability theory. Probabilis…
Projection Predictive Inference for Generalized Linear and Additive Multilevel Models
Alejandro Catalina, Paul-Christian Bürkner, Aki Vehtari
Projection predictive inference is a decision theoretic Bayesian approach that decouples model estimation from decision making. Given a reference model previously built including a…