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Entropy 2017, 19(10), 564; https://doi.org/10.3390/e19100564

Prior Elicitation, Assessment and Inference with a Dirichlet Prior

Department of Statistical Sciences, University of Toronto, Toronto, ON M5S 3G3, Canada
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Received: 29 July 2017 / Revised: 12 October 2017 / Accepted: 20 October 2017 / Published: 22 October 2017
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Abstract

Methods are developed for eliciting a Dirichlet prior based upon stating bounds on the individual probabilities that hold with high prior probability. This approach to selecting a prior is applied to a contingency table problem where it is demonstrated how to assess the prior with respect to the bias it induces as well as how to check for prior-data conflict. It is shown that the assessment of a hypothesis via relative belief can easily take into account what it means for the falsity of the hypothesis to correspond to a difference of practical importance and provide evidence in favor of a hypothesis. View Full-Text
Keywords: elicitation; bias; prior-data conflict; relative belief inferences; multinomial distribution; Dirichlet prior elicitation; bias; prior-data conflict; relative belief inferences; multinomial distribution; Dirichlet prior
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Evans, M.; Guttman, I.; Li, P. Prior Elicitation, Assessment and Inference with a Dirichlet Prior. Entropy 2017, 19, 564.

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