A Heavily Right Strategy for Statistical Inference with Dependent Studies in Arbitrary Dimensions
任意维度下依赖研究推断的重右尾策略
We leverage recent advances in heavy-tail approximations for global hypothesis testing with dependent studies to construct approximate confidence regions without modeling or estimating their dependence structures. A non-rejection region is a confidence region but it may not be convex. Convexity is appealing because it ensures any one-dimensional linear projection of the region is a confidence interval, easy to compute and interpret. We show why convexity fails for nearly all…