False discovery control for random fields \
False discovery control for random fields \
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DOI：
10.1198/0162145000001655
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发表时间：
2004-12-01
影响因子：
3.7
通讯作者：
Wasserman, L
中科院分区：
文献类型：
--
作者：
Pacifico, MP;Genovese, C;Wasserman, L
本文将错误发现率扩展到随机域。有无数的假设检验我们开发了一种方法，用于在该领域的域中找到区域，其中有一个显着的信号，同时控制区域的比例或发生错误拒绝的集群的比例。该方法产生作为拒绝阈值的函数的错误发现的比例的置信包络。从置信包络，我们得到阈值程序来控制的平均值或指定的尾部概率的错误发现的比例。这个函数的一个重要组成部分是一个新的算法来计算所有真空位置的置信超集。我们展示了我们的方法与应用程序扫描统计和功能神经成像。
This article extends false discovery rates to random fields. for which there are uncountably many hypothesis tests. We develop a method for finding regions in the field's domain where there is a significant signal while controlling either the proportion of area or the proportion of clusters in which false rejections occur. The method produces confidence envelopes for the proportion of false discoveries as a function of the rejection threshold. From the confidence envelopes, we derive threshold procedures to control either the mean or the specified tail probabilities of the false discovery proportion. An essential ingredient of this construnction is a new algorithm to compute a confidence superset for the set of all true-null locations. We demonstrate our method with applications to scan statistics and functional neuroimaging.