A Philosopher’s View on Bayesian Evaluation of Informative Hypotheses
This chapter provides an answer to the question: What it is, philosophically speaking, to choose a model in a statistical procedure, and what does this amounts to in the context of a Bayesian inference? Special attention is given to Bayesian model selection, specifically the choice between inequality constrained and unconstrained models based on their Bayes factors and posterior model probabilities.
KeywordsBayesian Inference Inductive Inference Bayesian Statistic Probability Assignment Logical Possibility
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- Carnap, R.: The Foundations of Probability. Chicago, University of Chicago Press (1950)Google Scholar
- Cover, J.A., Curd, M.: Philosophy of Science: The Central Issues. New York , Norton and Co. (1998)Google Scholar
- Goodman, N.: Fact, Fiction, and Forecast. Cambridge (MA), Harvard University Press (1955)Google Scholar
- Hintikka, J.: A Two–dimensional Continuum of Inductive Methods. In: Hintikka, J., Suppes, P. (eds) Aspects of Inductive Logic. Amsterdam, North Holland (1966)Google Scholar
- Hume, D.: An Enquiry concerning human understanding (1748). Tom Beauchamp (ed), Oxford, Oxford University Press (1999)Google Scholar
- Romeijn, J.W.: Bayesian inductive logic. Ph.D. thesis, University of Groningen (2005)Google Scholar