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Synthese

, Volume 156, Issue 1, pp 53–77 | Cite as

Bayesian Confirmation Theory and The Likelihood Principle

  • Daniel SteelEmail author
Article

Abstract

The likelihood principle (LP) is a core issue in disagreements between Bayesian and frequentist statistical theories. Yet statements of the LP are often ambiguous, while arguments for why a Bayesian must accept it rely upon unexamined implicit premises. I distinguish two propositions associated with the LP, which I label LP1 and LP2. I maintain that there is a compelling Bayesian argument for LP1, based upon strict conditionalization, standard Bayesian decision theory, and a proposition I call the practical relevance principle. In contrast, I argue that there is no similarly compelling argument for or against LP2. I suggest that these conclusions lead to a restrictedly pluralistic view of Bayesian confirmation measures.

Keywords

Likelihood Function Inductive Inference Identical Alternative Likelihood Principle Causal Decision Theory 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer 2007

Authors and Affiliations

  1. 1.Department of PhilosophyMichigan State UniversityEast LansingUSA

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