Two discussions of the paper "Bayesian measures of model complexity and fit" by D. Spiegelhalter et al., Read before The Royal Statistical Society at a meeting organized by the Research Section on Wednesday, March 13th, 2002

TL;DR

This paper presents discussions on Bayesian measures of model complexity and fit, highlighting their implications and applications in statistical modeling, based on a presentation at a major statistical society meeting.

Contribution

It provides expert commentary and insights on the original Bayesian measures paper, emphasizing practical considerations and potential extensions.

Findings

Highlights the importance of Bayesian measures in model assessment

Discusses the applicability of Bayesian complexity in real-world data analysis

Suggests avenues for future research in Bayesian model evaluation

Abstract

These are the written discussions of the paper "Bayesian measures of model complexity and fit" by D. Spiegelhalter et al. (2002), following the discussions given at the Annual Meeting of the Royal Statistical Society in Newcastle-upon-Tyne on September 3rd, 2013.