Mathematical Sciences: Topics in Statistical Theory

伯克教授将专注于测试在一个互动 数据不平衡的双向表，这是一个没有 迄今为止令人满意的无分布解决方案。 辛格教授 我将继续研究恢复方法， 将方向性数据按中心性排序。 这 等级提供了球体上的中值的自然概念。 他 还将研究效率的渐近下界， 估计器和自适应估计。 刘教授追求 关于单纯形深度的问题。 将研究统计理论中的几个主题。 潜在的影响包括扩大适用范围， 分类数据和稀疏数据的统计方法 结构.

Professor Berk will focus on testing for interaction in a two-way table with unbalanced data, a problem that has no satisfactory distribution-free solution to date. Professor Singh will continue work on resampling methods by introducing the idea of ranking directional data in the order of centrality. This ranking provides a natural concept of the median on a sphere. He will also work on asymptotic lower bounds of efficiency for estimators and adaptive estimation. Professor Liu pursues questions related to the notion of simplicial depth. Several topics in statistical theory will be investigated. The potential impact includes a broadening of the applicability of statistical methods for categorical data and for sparse data structures.