A Bayesian analysis of classical hypothesis testing
A Bayesian analysis of classical hypothesis testing
复制标题
经典假设检验的贝叶斯分析
DOI：
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发表时间：
1980
期刊：
影响因子：
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通讯作者：
J. Bernardo
中科院分区：
文献类型：
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作者：
J. Bernardo
摘要应用最大化缺失信息的过程来获得零假设的参考后验概率。结果揭示了进一步阐明林德利的悖论，并建议经典的假设检验的贝叶斯解释是可能的，通过提供一个一对一的近似关系的显着性水平和后验概率。
SummaryThe procedure of maximizing the missing information is applied to derive reference posterior probabilities for null hypotheses. The results shed further light on Lindley’s paradox and suggest that a Bayesian interpretation of classical hypothesis testing is possible by providing a one-to-one approximate relationship between significance levels and posterior probabilities.