Last updated: 2018-05-14

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Building on Prof. Matthew Stephens’s initial observation that under correlation, although the empirical distributions of the test statistics are different from their theoretical marginal one, correlation affacts test statistics unevenly. Moderate observations, defined as \(|\hat\beta / \hat s| \leq t\) with a pre-specified \(t\), are more prone to correlation and thus contain less information to control false discoveries than extreme ones, truncash makes partial use of moderate observations, combined with full use of extreme ones, for adaptive empirical Bayes shrinkage.


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