文章基本信息

标题：Bayesian inference in partially identified models: Is the shape of the posterior distribution useful?
本地全文：下载
作者：Paul Gustafson
期刊名称：Electronic Journal of Statistics
印刷版ISSN：1935-7524
出版年度：2014
卷号：8
期号：1
页码：476-496
DOI：10.1214/14-EJS891
语种：English
出版社：Institute of Mathematical Statistics
摘要：Partially identified models are characterized by the distribution of observables being compatible with a set of values for the target parameter, rather than a single value. This set is often referred to as an identification region. From a non-Bayesian point of view, the identification region is the object revealed to the investigator in the limit of increasing sample size. Conversely, a Bayesian analysis provides the identification region plus the limiting posterior distribution over this region. This purports to convey varying plausibility of values across the region. Taking a decision-theoretic view, we investigate the extent to which having a distribution across the identification region is indeed helpful.
关键词：Bayesian inference;partial identification;pos terior distribution.