Geometry of rank tests
Jason Morton, Lior Pachter, Anne Shiu, Bernd Sturmfels, Oliver Wienand
Abstract
We study partitions of the symmetric group which have desirable geometric properties. The statistical tests defined by such partitions involve counting all permutations in the equivalence classes. These permutations are the linear extensions of partially ordered sets specified by the data. Our methods refine rank tests of non-parametric statistics, such as the sign test and the runs test, and are useful for the exploratory analysis of ordinal data. Convex rank tests correspond to probabilistic conditional independence structures known as semi-graphoids. Submodular rank tests are classified by the faces of the cone of submodular functions, or by Minkowski summands of the permutohedron. We enumerate all small instances of such rank tests. Graphical tests correspond to both graphical models and to graph associahedra, and they have excellent statistical and algorithmic properties.
Create a lesson
Related papers
Conformal Prediction Through the Lens of Hypothesis Testing: Universality, Impossibility, and Optimality
Ryan J. Tibshirani, Rina Foygel Barber, Aaditya Ramdas
Connecting Riemannian Geometry and Statistical Inference for Correlation Matrices
Argyn Kuketayev
How far can symmetry help? Phase transitions and symmetry selection in sparse functional data analysis
Jocelyn Nembe
Posterior consistency for subdiffusion inverse problems
Haoyu Lu, Shaokang Zu, Junxiong Jia
Dimension comparison for Student's statistic under symmetric unimodality
Jacopo Lenzi
Statistical Properties of Nonparametric MLE under Laplace Noise
Yifei Xiong, Nianqiao Phyllis Ju, Vinayak Rao