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Theory Change and Bayesian Statistical Inference

Published online by Cambridge University Press:  01 January 2022

Abstract

This paper addresses the problem that Bayesian statistical inference cannot accommodate theory change, and proposes a framework for dealing with such changes. It first presents a scheme for generating predictions from observations by means of hypotheses. An example shows how the hypotheses represent the theoretical structure underlying the scheme. This is followed by an example of a change of hypotheses. The paper then presents a general framework for hypotheses change, and proposes the minimization of the distance between hypotheses as a rationality criterion. Finally the paper discusses the import of this for Bayesian statistical inference.

Type
Decision Theory
Copyright
Copyright © The Philosophy of Science Association

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References

Dawid, A. P. (1982), “The Well-Calibrated Bayesian”, The Well-Calibrated Bayesian 77:605613.Google Scholar
Earman, J. (1992), Bayes or Bust. Cambridge, MA: MIT Press.Google Scholar
Gillies, D. (2001), “Bayesianism and the Fixity of the Theoretical Framework”, in Corfield, D. and Williamson, J. (eds.), Foundations of Bayesianism. Dordrecht: Kluwer, 363379.CrossRefGoogle Scholar
Kullback, S. (1959), Information Theory and Statistics. New York: Wiley.Google Scholar
Paris, J. (1994), The Uncertain Reasoner’s Companion. Cambridge: Cambridge University Press.Google Scholar
Williamson, J. (2003), “Bayesianism and Language Change”, Bayesianism and Language Change 12:5397.Google Scholar