Document Type
Discussion Paper
Publication Date
8-1-1990
CFDP Number
951
CFDP Pages
16
Abstract
This paper shows how the modern machinery for generating abstract empirical central limit theorems can be applied to arrays of dependent variables. It develops a bracketing approximation based on a moment inequality for sums of strong mixing arrays, in an effort to illustrate the sorts of difficulty that need to be overcome when adapting the empirical process theory for independent variables. Some suggestions for further development are offered. The paper is largely self-contained.
Recommended Citation
Andrews, Donald W.K. and Pollard, David, "A Functional Central Limit Theorem for Strong Mixing Stochastic Processes" (1990). Cowles Foundation Discussion Papers. 1194.
https://elischolar.library.yale.edu/cowles-discussion-paper-series/1194