Sequential selection procedures and false discovery rate control
Sequential selection procedures and false discovery rate control
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DOI：
10.1111/rssb.12122
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发表时间：
2016-03-01
影响因子：
5.8
通讯作者：
Tibshirani, Robert
中科院分区：
文献类型：
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作者：
G'Sell, Max Grazier;Wager, Stefan;Tibshirani, Robert
我们考虑多重假设检验设置，其中假设是排序的，并且只允许拒绝假设的初始连续块H1，...，Hk。此设置中的拒绝规则相当于选择停止点k的过程。此设置的灵感来自许多模型选择问题的顺序性质，其中选择停止点或模型相当于拒绝该点之前的所有假设，之后则不拒绝任何假设。我们提出了两种新的测试方法，并证明了它们在有序测试环境下控制了错误发现率。我们还展示了如何通过使用序列模型选择设置中关于p值的最新结果来将这些方法应用于模型选择。
We consider a multiple-hypothesis testing setting where the hypotheses are ordered and one is only permitted to reject an initial contiguous block H1,...,Hk of hypotheses. A rejection rule in this setting amounts to a procedure for choosing the stopping point k. This setting is inspired by the sequential nature of many model selection problems, where choosing a stopping point or a model is equivalent to rejecting all hypotheses up to that point and none thereafter. We propose two new testing procedures and prove that they control the false discovery rate in the ordered testing setting. We also show how the methods can be applied to model selection by using recent results on p-values in sequential model selection settings.