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Bayesian analysis of seasonal variation when the sample size and the amplitude are small

机译:样本量和振幅较小时的季节性变化的贝叶斯分析

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We propose what appears to be the first Bayesian procedure for the analysis of seasonal variation when the sample size and the amplitude are small. Such data occur often in the medical sciences, where seasonality analyses and environmental considerations can help clarify disease etiologies. The method is explained in terms of a simple physico-geometric setting. We present the Bayesian version of a frequentist test that performs well. Two examples of real data illustrate the procedure's application.
机译:当样本量和振幅较小时,我们提出了似乎是用于分析季节变化的第一个贝叶斯程序。这样的数据经常出现在医学领域,其中季节性分析和环境因素可以帮助弄清疾病的病因。根据简单的物理几何设置来说明该方法。我们提出了表现良好的贝叶斯版本的频繁测试。真实数据的两个示例说明了该过程的应用。

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