Multiple Hypothesis Testing on an Aggregation Tree Method

An implementation of the TEAM algorithm to identify local differences between two (e.g. case and control) independent, univariate distributions, as described in J Pura, C Chan, and J Xie (2019) . The algorithm is based on embedding a multiple-testing procedure on a hierarchical structure to identify high-resolution differences between two distributions. The hierarchical structure is designed to identify strong, short-range differences at lower layers and weaker, but long-range differences at increasing layers. TEAM yields consistent layer-specific and overall false discovery rate control.