Multiple Bayes Factors for Testing Hypotheses
作者:
Francesco Bertolino,
Ludovico Piccinato,
Walter Racugno,
期刊:
Journal of the American Statistical Association
(Taylor Available online 1995)
卷期:
Volume 90,
issue 429
页码: 213-219
ISSN:0162-1459
年代: 1995
DOI:10.1080/01621459.1995.10476504
出版商: Taylor & Francis Group
关键词: Hierarchical priors;Monotone priors;Multiple hypotheses;Quantile constraints;Robustness
数据来源: Taylor
摘要:
Partial and multiple Bayes factors are introduced to obtain pairwise comparisons of hypotheses in a statistical experiment with a partition on the parameter space. Robust Bayesian analyses are performed by introducing suitable classes of priors and by calculating lower and upper bounds of Bayes factors and posterior probabilities. Classes of intuitively meaningful priors are introduced, including unimodal densities without the constraint of symmetry for the case of precise hypotheses. Procedures for the corresponding optimizations are specified, and examples are given.
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