Prior Elicitation, Assessment and Inference with a Dirichlet Prior
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 bia...
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MDPI AG
2017-10-01
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| Series: | Entropy |
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| Online Access: | https://www.mdpi.com/1099-4300/19/10/564 |
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doaj-05af1699d5204c51afa8ca403ae68ece2020-11-24T21:51:19ZengMDPI AGEntropy1099-43002017-10-01191056410.3390/e19100564e19100564Prior Elicitation, Assessment and Inference with a Dirichlet PriorMichael Evans0Irwin Guttman1Peiying Li2Department of Statistical Sciences, University of Toronto, Toronto, ON M5S 3G3, CanadaDepartment of Statistical Sciences, University of Toronto, Toronto, ON M5S 3G3, CanadaDepartment of Statistical Sciences, University of Toronto, Toronto, ON M5S 3G3, CanadaMethods 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.https://www.mdpi.com/1099-4300/19/10/564elicitationbiasprior-data conflictrelative belief inferencesmultinomial distributionDirichlet prior |
| collection |
DOAJ |
| language |
English |
| format |
Article |
| sources |
DOAJ |
| author |
Michael Evans Irwin Guttman Peiying Li |
| spellingShingle |
Michael Evans Irwin Guttman Peiying Li Prior Elicitation, Assessment and Inference with a Dirichlet Prior Entropy elicitation bias prior-data conflict relative belief inferences multinomial distribution Dirichlet prior |
| author_facet |
Michael Evans Irwin Guttman Peiying Li |
| author_sort |
Michael Evans |
| title |
Prior Elicitation, Assessment and Inference with a Dirichlet Prior |
| title_short |
Prior Elicitation, Assessment and Inference with a Dirichlet Prior |
| title_full |
Prior Elicitation, Assessment and Inference with a Dirichlet Prior |
| title_fullStr |
Prior Elicitation, Assessment and Inference with a Dirichlet Prior |
| title_full_unstemmed |
Prior Elicitation, Assessment and Inference with a Dirichlet Prior |
| title_sort |
prior elicitation, assessment and inference with a dirichlet prior |
| publisher |
MDPI AG |
| series |
Entropy |
| issn |
1099-4300 |
| publishDate |
2017-10-01 |
| description |
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. |
| topic |
elicitation bias prior-data conflict relative belief inferences multinomial distribution Dirichlet prior |
| url |
https://www.mdpi.com/1099-4300/19/10/564 |
| work_keys_str_mv |
AT michaelevans priorelicitationassessmentandinferencewithadirichletprior AT irwinguttman priorelicitationassessmentandinferencewithadirichletprior AT peiyingli priorelicitationassessmentandinferencewithadirichletprior |
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1725879135131140096 |