Objective priors for the bivariate normal model
نویسندگان
چکیده
منابع مشابه
Objective Priors for the Bivariate Normal Model
Study of the bivariate normal distribution raises the full range of issues involving objective Bayesian inference, including the different types of objective priors (e.g., Jeffreys, invariant, reference, matching), the different modes of inference (e.g., Bayesian, frequentist, fiducial) and the criteria involved in deciding on optimal objective priors (e.g., ease of computation, frequentist per...
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Study of the bivariate normal distribution raises the full range of issues involving objective Bayesian inference, including the different types of objective priors (e.g., Jeffreys, invariant, reference, matching), the different modes of inference (e.g., Bayesian, frequentist, fiducial), and the criteria involved in deciding on optimal objective priors (e.g., ease of computation, frequentist pe...
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Informative Bayesian priors are often difficult to elicit, and when this is the case, modelers usually turn to noninformative or objective priors. However, objective priors such as the Jeffreys and reference priors are not tractable to derive for many models of interest. We address this issue by proposing techniques for learning reference prior approximations: we select a parametric family and ...
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ژورنال
عنوان ژورنال: The Annals of Statistics
سال: 2008
ISSN: 0090-5364
DOI: 10.1214/07-aos501