Nonparametric K -Sample Tests via Dynamic Slicing
基于动态切片的非参数多样本检验
K-sample testing problems arise in many scientific applications and have attracted statisticians’ attention for many years. We propose an omnibus nonparametric method based on an optimal discretization (aka “slicing”) of continuous random variables in the test. The novelty of our approach lies in the inclusion of a term penalizing the number of slices (i.e., the resolution of the discretization) so as to regularize the corresponding likelihood-ratio test statistic. An…