Order Statistics for Nonstationary Time series

Abstract

Order statistics has an important role in statistical inference. The main purpose of this paper is to investigate order statistics, and also explore its applications in the analysis of nonstationary time series. Our results show that linear functions of order statistics for a large class of time series are asymptotically normal. The methods of proof involve approximations of serially dependent random variables by independent ones. The problems of testing for the existence of a linear trend and the problem of testing randomness versus serial dependence are considered as applications.