Villa, Cristiano, Walker, Stephen (2015) An Objective Approach to Prior Mass Functions for Discrete Parameter Spaces. Journal of the American Statistical Association, 110 (511). pp. 1072-1082. ISSN 0162-1459. E-ISSN 1537-274X. (doi:10.1080/01621459.2014.946319) (Access to this publication is currently restricted. You may be able to access a copy if URLs are provided) (KAR id:43476)
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Official URL: http://dx.doi.org/10.1080/01621459.2014.946319 |
Abstract
We present a novel approach to constructing objective prior distributions for discrete pa- rameter spaces. These type of parameter spaces are particularly problematic, as it appears that common objective procedures to design prior distributions are problem specific. We propose an objective criterion, based on loss functions, instead of trying to define objective probabilities directly. We systematically apply this criterion to a series of discrete scenarios, previously considered in the literature, and compare the priors. The proposed approach applies to any discrete parameter space, making it appealing as it does not involve different concepts according to the model. This article has supplementary material online.
Item Type: | Article |
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DOI/Identification number: | 10.1080/01621459.2014.946319 |
Uncontrolled keywords: | Binomial, Discrete parameter space, Hypergeometric, Kullback–Leibler divergence, Loss function, Objective prior |
Subjects: | Q Science > QA Mathematics (inc Computing science) > QA276 Mathematical statistics |
Divisions: | Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Mathematics, Statistics and Actuarial Science |
Depositing User: | Cristiano Villa |
Date Deposited: | 18 Oct 2014 22:37 UTC |
Last Modified: | 17 Aug 2022 10:57 UTC |
Resource URI: | https://kar.kent.ac.uk/id/eprint/43476 (The current URI for this page, for reference purposes) |
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