JSM 2005 - Toronto

Abstract #302967

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Legend: = Applied Session, = Theme Session, = Presenter
Activity Number: 103
Type: Contributed
Date/Time: Monday, August 8, 2005 : 8:30 AM to 10:20 AM
Sponsor: IMS
Abstract - #302967
Title: On the Accuracy of Bootstrapping Sample Quantiles of Strongly Mixing Sequences
Author(s): Shuxia Sun*+
Companies: Wright State University
Address: 159 MM, Dayton, OH, 45435, United States
Keywords: moving block bootstrap ; sample quantile ; strictly stationary ; strongly mixing ; weakly dependent
Abstract:

In this paper, we examine the rate of convergence of the moving block bootstrap (MBB) approximations to distributions of normalized sample quantiles based on strongly mixing observations. Under suitable smoothness and regularity conditions on the one-dimensional marginal distribution function, the MBB approximation to the distribution of sample quantiles of weakly dependent random variables has the same accuracy as Efron's bootstrap approximation to the distribution of sample quantiles based on independent observations. Our result extends Theorem 2 of Singh (1981).


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