期刊
ELECTRONIC JOURNAL OF STATISTICS
卷 8, 期 -, 页码 476-496出版社
INST MATHEMATICAL STATISTICS
DOI: 10.1214/14-EJS891
关键词
Bayesian inference; partial identification; posterior distribution
资金
- Natural Sciences and Engineering Research Council of Canada
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. Prom 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 limit big 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.
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