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An Objective Approach to Prior Mass Functions for Discrete Parameter Spaces

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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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
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: Faculties > Sciences > School of Mathematics Statistics and Actuarial Science > Statistics
Depositing User: Cristiano Villa
Date Deposited: 18 Oct 2014 22:37 UTC
Last Modified: 17 Jan 2020 15:57 UTC
Resource URI: (The current URI for this page, for reference purposes)
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