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A INVITED PAPERS
CASTILLO E LAVACHI I
NATALE M London SWI7
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Akaike application approximation assessment assumed assumption axioms Bayes estimates Bayes factor Bayes procedure Bayesian analysis Bayesian approach Bayesian inference Bayesian statistics choice clinical trial coherence conditional consider covariance D.V. Lindley Dawid decision maker decision problem defined DeGroot denotes density depend Dickey Dirichlet discrepancy function discussion estimation example Finetti finitely additive forecasting given hyperparameters hypothesis improper prior independent involved Kadane least squares likelihood function likelihood principle Lindley linear model loss function Makov marginal mathematical matrix maximum likelihood method mixture multivariate normal distribution nuisance parameters observations obtained opinion outliers paper partial ignorance particular patient pivotal possible posterior distribution posterior mean posterior probability predictive distribution prior distribution prior probability probability measures Professor quasi-Bayesian question random ratio reason REFERENCES sample significance test situation Smith specify statistician structure subjective probability Suppose theorem theory treatment University utility function variables variance vector Zellner