Integral Priors and Constrained Imaginary Training Samples for Nested and Non-nested Bayesian Model Comparison
[摘要] In Bayesian model selection when the prior information on the parameters of the models is vague default priors should be used. Unfortunately, these priors are usually improper yielding indeterminate Bayes factors that preclude the comparison of the models
[发布日期] [发布机构]
[效力级别] [学科分类] 统计和概率
[关键词] Bayesian model selection;Bayes factor;intrinsic priors;integral priors [时效性]
