Bayesian and non-Bayesian approaches to statistical inference and decision-making

Bayesian and non-Bayesian approaches to statistical inference and decision-making are discussed and compared. A pragmatic criterion, success in practice, as well as logical consistency are emphasized in comparing alternative approaches. Attention is given to learning models, probability concepts, prior information, axiom systems and selected technical aspects of Bayesian and non-Bayesian approaches.

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