论文检索

利用代表性子群提高精确群不变性检验效率AI 解读

Summary We consider testing invariance of a distribution under an algebraic group of transformations, such as permutations or sign flips. As such groups are typically huge, tests based on the full group are often computationally infeasible. Hence, it is standard practice to use a random subset of transformations. We improve upon this by replacing the random subset with a strategically chosen, fixed subgroup of transformations. In a generalized location model, we show that…

基于置换的错误发现比例同时置信界AI 解读

Summary When multiple hypotheses are tested, interest is often in ensuring that the proportion of false discoveries is small with high confidence. In this paper, confidence upper bounds for the false discovery proportion are constructed, which are simultaneous over all rejection cut-offs. In particular, this allows the user to select a set of hypotheses post hoc such that the false discovery proportion lies below some constant with high confidence. Our method uses…