The Distributions of Smirnov-Type Two-Sample Rank Tests for Discontinuous Distribution Functions

An adaptive algorithm for clustering cumulative probability distribution functions using the Kolmogorov-Smirnov two-sample test

This paper proposes an adaptive algorithm for clustering cumulative probability distribution functions (c.p.d.f.) of a continuous random variable, observed in different populations, into the minimum homogeneous clusters, making no parametric assumptions about the c.p.d.f.’s. The distance function for clustering c.p.d.f.’s that is proposed is based on the KolmogorovSmirnov two sample statistic. ...

On Some Questions Connected with Two-sample Tests of Smirnov Type

Two-sample smooth tests for the equality of distributions

WEN-XIN ZHOU1,2,* , CHAO ZHENG2,** and ZHEN ZHANG3 1Department of Operations Research and Financial Engineering, Princeton University, Princeton, NJ 08544, USA. E-mail: *[email protected] 2School of Mathematics and Statistics, University of Melbourne, Parkville, VIC 3010, Australia. E-mail: **[email protected] 3Department of Statistics, University of Chicago, Chicago, IL 60637,...

Symmetrized Approximate Score Rank Tests for the Two-sample Case

Max-type rank tests, U-tests, and adaptive tests for the two-sample location problem - An asymptotic power study

For the two-sample location problem we first consider two types of tests, linear rank tests with various scores, but also some tests based on U-statistics. For both types we construct adaptive tests as well as max-type tests and investigate their asymptotic and finite power properties. It turns out that both the adaptive tests have larger asymptotic power than the max-type tests. For small samp...