An Objective Approach to Prior Mass Functions for Discrete Parameter Spaces

成果类型:
Article
署名作者:
Villa, C.; Walker, S. G.
署名单位:
University of Kent; University of Texas System; University of Texas Austin; University of Texas System; University of Texas Austin
刊物名称:
JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION
ISSN/ISSBN:
0162-1459
DOI:
10.1080/01621459.2014.946319
发表日期:
2015
页码:
1072-1082
关键词:
posterior distributions number
摘要:
We present a novel approach to constructing objective prior distributions for discrete parameter spaces. These types 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. Supplementary materials for this article are available online.