We develop a framework for model criticism. Our approach is based on embedding a given model via the addition of an elaboration parameter. The value of an elaborated model is defined by the change in expected utility associated with updating the probability distribution on the elaboration parameter. This provides the experimenter with a numerical summary for model criticism. Our approach offers a unified framework for probing assumptions on which probability modelling is based. Model criticism is performed enterely within the Baysian framework. We explore relationships with other diagnostic measures, namely Fisher's score function, deviance and the Bayes factor

Bayesian Model Criticism

CAROTA, Cinzia;
1993-01-01

Abstract

We develop a framework for model criticism. Our approach is based on embedding a given model via the addition of an elaboration parameter. The value of an elaborated model is defined by the change in expected utility associated with updating the probability distribution on the elaboration parameter. This provides the experimenter with a numerical summary for model criticism. Our approach offers a unified framework for probing assumptions on which probability modelling is based. Model criticism is performed enterely within the Baysian framework. We explore relationships with other diagnostic measures, namely Fisher's score function, deviance and the Bayes factor
1993
Annual Meeting of the American Statistcal Association
San Francisco
August 8-12
Proceedings of the Section on Bayesian Statistical Science at the Annual Meeting of the American Statistical Association
American Statistical Association
22
27
Information; model specification; prior influence; score function; Bayes factor; residuals; outliers; hierarchical models
C. Carota; G. Parmigiani
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2318/114050
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