Bayesian decision theory, subjective and objective probabilities, and acceptance of empirical hypotheses
David Bourget (Western Ontario)
David Chalmers (ANU, NYU)
Rafael De Clercq
Jack Alan Reynolds
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Synthese 57 (3):341 - 365 (1983)
It is argued that we need a richer version of Bayesian decision theory, admitting both subjective and objective probabilities and providing rational criteria for choice of our prior probabilities. We also need a theory of tentative acceptance of empirical hypotheses. There is a discussion of subjective and of objective probabilities and of the relationship between them, as well as a discussion of the criteria used in choosing our prior probabilities, such as the principles of indifference and of maximum entropy, and the simplicity ranking of alternative hypotheses.
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References found in this work BETA
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Harold Jeffreys (1973). Scientific Inference. Cambridge [Eng.]Cambridge University Press.
Citations of this work BETA
Daniel Steel (forthcoming). Acceptance, Values, and Probability. Studies in History and Philosophy of Science Part A.
Sven Ove Hansson (2007). Values in Pure and Applied Science. Foundations of Science 12 (3):257-268.
John C. Harsanyi (1985). Acceptance of Empirical Statements: A Bayesian Theory Without Cognitive Utilities. Theory and Decision 18 (1):1-30.
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R. Festa (1993). Optimum Inductive Methods. Kluwer Academic Publishers: Dordrecht.
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