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- W1662363606 abstract "Inferences that arise from loss functions determined by the prior are considered and it is shown that these lead to limiting Bayes rules that are closely connected with likelihood. The procedures obtained via these loss functions are invariant under reparameterizations and are Bayesian unbiased or limits of Bayesian unbiased inferences. These inferences serve as well-supported alternatives to MAP-based inferences." @default.
- W1662363606 created "2016-06-24" @default.
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- W1662363606 date "2011-04-16" @default.
- W1662363606 modified "2023-09-27" @default.
- W1662363606 title "Inferences from prior-based loss functions" @default.
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