In Arnold Zellner, Hugo A. Keuzenkamp & Michael McAleer (eds.), Simplicity, Inference, and Modelling. Cambridge: Cambridge University Press. pp. 13-32 (2002)
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The problem of simplicity involves three questions: How is the simplicity of a hypothesis to be measured? How is the use of simplicity as a guide to hypothesis choice to be justified? And how is simplicity related to other desirable features of hypotheses -- that is, how is simplicity to be traded-off? The present paper explores these three questions, from a variety of viewpoints, including Bayesianism, likelihoodism, and the framework of predictive accuracy formulated by Akaike (1973). It may turn out that simplicity has no global justification -- that its justification varies from problem to problem.
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Bayesian Generic Priors for Causal Learning.Hongjing Lu, Alan L. Yuille, Mimi Liljeholm, Patricia W. Cheng & Keith J. Holyoak - 2008 - Psychological Review 115 (4):955-984.
Getting It Right.Kristoffer Ahlstrom-Vij & Stephen R. Grimm - 2013 - Philosophical Studies 166 (2):329-347.
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