B1031
Title: A high dimensional Cramer-von Mises test
Authors: Danna Zhang - University of California, San Diego (United States)
Mengyu Xu - University of Central Florida (United States) [presenting]
Abstract: The Cramer-von Mises test provides a useful criterion for assessing goodness-of-fit in various problems. A novel Cramer-von Mises type test is introduced for testing distributions of high-dimensional continuous data. An asymptotic theory is established for the proposed test statistics based on quadratic functions in high-dimensional stochastic processes. To estimate the limiting distribution of the test statistic, two practical approaches are proposed: a plug-in calibration method and a subsampling method. Theoretical justifications are provided for both techniques. The numerical simulation also confirms the convergence of the proposed methods.
