This file is part of IDEAS, which uses RePEc data


[ Papers | Articles | Software | Books | Chapters | Authors | Institutions | JEL Classification | NEP reports | Search | New papers by email | Author registration | Rankings | Volunteers | FAQ | Blog | Help! ]

A Functional Central Limit Theorem for Strong Mixing Stochastic Processes

Author info | Abstract | Publisher info | Download info | Related research | Statistics
Author Info
Donald W.K. Andrews () (Cowles Foundation, Yale University)
David Pollard (Dept. of Statistics, Yale University)

Additional information is available for the following registered author(s):

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.

Download Info
To download:

If you experience problems downloading a file, check if you have the proper application to view it first. Information about this may be contained in the File-Format links below. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.

File URL: http://cowles.econ.yale.edu/P/cp/p08b/p0870.pdf
File Format: application/pdf
File Function:
Download Restriction: no
File URL: http://cowles.econ.yale.edu/P/cd/d09b/d0951.pdf
File Format: application/pdf
File Function:
Download Restriction: no

Publisher Info
Paper provided by Cowles Foundation, Yale University in its series Cowles Foundation Discussion Papers with number 951.

Download reference. The following formats are available: HTML (with abstract), plain text (with abstract), BibTeX, RIS (EndNote, RefMan, ProCite), ReDIF
Length: 16 pages
Date of creation: Sep 1990
Date of revision:
Publication status: Published in International Statistical Review (1994), 62(1): 119-132
Handle: RePEc:cwl:cwldpp:951

Note: CFP 870.
Contact details of provider:
Postal: Yale University, Box 208281, New Haven, CT 06520-8281 USA
Phone: (203) 432-3702
Fax: (203) 432-6167
Web page: http://cowles.econ.yale.edu/
More information through EDIRC

Order Information:
Postal: Cowles Foundation, Yale University, Box 208281, New Haven, CT 06520-8281 USA

For technical questions regarding this item, or to correct its listing, contact: (Glena Ames).

Related research
Keywords: Strong mixing; functional central limit theorem; empirical process;

References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:

  1. Donald W.K. Andrews, 1989. "An Empirical Process Central Limit Theorem for Dependent Non-Identically Distributed Random Variables," Cowles Foundation Discussion Papers 907, Cowles Foundation, Yale University. [Downloadable!]
    Other versions:
  2. Donald W.K. Andrews, 1989. "Asymptotics for Semiparametric Econometric Models: I. Estimation," Cowles Foundation Discussion Papers 908R, Cowles Foundation, Yale University, revised Aug 1990. [Downloadable!]
  3. Donald W.K. Andrews, 1989. "Asymptotics for Semiparametric Econometric Models: II. Stochastic Equicontinuity and Nonparametric Kernel Estimation," Cowles Foundation Discussion Papers 909R, Cowles Foundation, Yale University, revised Jul 1990. [Downloadable!]
  4. Yukich, J. E., 1986. "Rates of convergence for classes of functions: The non-i.i.d. case," Journal of Multivariate Analysis, Elsevier, vol. 20(2), pages 175-189, December. [Downloadable!] (restricted)
Full references

Statistics
Access and download statistics

Did you know? About five million pdf files are downloaded through RePEc every year.

This page was last updated on 2009-12-22.

This information is provided to you by IDEAS at the Department of Economics, College of Liberal Arts and Sciences, University of Connecticut using RePEc data on a server sponsored by the Society for Economic Dynamics.