Publications [#257819] of Merlise Clyde
Chapters
- Clydec, M; Iversen, ES. "Bayesian model averaging in the M-open framework." Bayesian Theory and Applications.
Ed. Damien, P; Dellaportas, P; Polson, NG; Stephens, DA Oxford University Press, January, 2013: 483-498. [repository], [doi]
(last updated on 2026/01/14)Abstract:
This chapter presents a model averaging approach in the M-open setting using sample re-use methods to approximate the predictive distribution of future observations. It first reviews the standard M-closed Bayesian Model Averaging approach and decision-theoretic methods for producing inferences and decisions. It then reviews model selection from the M-complete and M-open perspectives, before formulating a Bayesian solution to model averaging in the M-open perspective. It constructs optimal weights for MOMA:M-open Model Averaging using a decision-theoretic framework, where models are treated as part of the ‘action space’ rather than unknown states of nature. Using ‘incompatible’ retrospective and prospective models for data from a case-control study, the chapter demonstrates that MOMA gives better predictive accuracy than the proxy models. It concludes with open questions and future directions.