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Optimal hypothesis testing: from semi to fully Bayes factors

机译:最佳假设检验:从半贝叶斯因子到完全贝叶斯因子

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摘要

We propose and examine statistical test-strategies that are somewhat between the maximum likelihood ratio and Bayes factor methods that are well addressed in the literature. The paper shows an optimality of the proposed tests of hypothesis. We demonstrate that our approach can be easily applied to practical studies, because execution of the tests does not require deriving of asymptotical analytical solutions regarding the type I error. However, when the proposed method is utilized, the classical significance level of tests can be controlled.
机译:我们提出并研究了统计测验策略,该策略在最大似然比和贝叶斯因子方法之间有些介于文献中。本文显示了所提出的假设检验的最优性。我们证明了我们的方法可以轻松地应用于实践研究,因为执行测试不需要派生关于I型错误的渐近分析解决方案。但是,当使用所提出的方法时,可以控制测试的经典显着性水平。

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