假设贝叶斯诊断的预测可信区域

T. Yanagimoto, Toshio Ohnishi
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引用次数: 2

摘要

根据e散度损失下的最优贝叶斯预测器,提出了诊断假设的AB贝叶斯方法。我们引入了一个预测可信区域作为后验可信区域的改进版本。在频域环境下,预测可信区域与似然比检验的拒绝区域的补足密切相关。作为一个应用,我们重新审视了关于林德利悖论的争议,并观察到与贝叶斯因子相比,所提出的可信区域具有令人满意的性能。另一个重要的应用涉及当假设被拒绝时分析额外证据的方法。
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PREDICTIVE CREDIBLE REGION FOR BAYESIAN DIAGNOSIS OF A HYPOTHESIS
AB ayesian method for diagnosing a hypothesis is proposed in terms of the optimum Bayesian predictor under the e-divergence loss. We introduce a predictive credible region as a modified version of a posterior credible region. The predictive credible region is closely related to the complement of the rejection region of the likelihood ratio test in the frequentist context. As an application we revisit the controversy regarding Lindley’s paradox, and observe satisfactory performance of the proposed credible region in contrast to the Bayes factor. Another important application concerns a method for analyzing additional evidence when a hypothesis is once rejected.
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