General Weak Laws of Large Numbers for Bootstrap Sample Means

CentER Discussion Paper Series No. 2004-112

18 Pages Posted: 4 Jan 2005

See all articles by John H. J. Einmahl

John H. J. Einmahl

Tilburg University - Department of Econometrics & Operations Research

Andrew Rosalsky

University of Florida - Department of Statistics

Date Written: October 2004

Abstract

For bootstrap sample means resulting from a sequence fXn; n 1g of random variables, very general weak laws of large numbers are established.The random variables fXn; n 1g do not need to be independent or identically distributed or to be of any particular dependence structure.In general, no moment conditions are imposed on the fXn; n 1g: Examples are provided which illustrate the sharpness of the main results.

Keywords: bootstrap sample mean, weak law of large numbers, convergence in probability, almost certain convergence

JEL Classification: C15

Suggested Citation

Einmahl, John H. J. and Rosalsky, Andrew, General Weak Laws of Large Numbers for Bootstrap Sample Means (October 2004). CentER Discussion Paper Series No. 2004-112, Available at SSRN: https://ssrn.com/abstract=639485 or http://dx.doi.org/10.2139/ssrn.639485

John H. J. Einmahl (Contact Author)

Tilburg University - Department of Econometrics & Operations Research ( email )

P.O. Box 90153
5000 LE Tilburg
Netherlands

Andrew Rosalsky

University of Florida - Department of Statistics ( email )

P.O. Box 118545
Gainesville, FL 32611-8545
United States
352-392-1941 (Phone)
352-392-5175 (Fax)

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