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On the accuracy of bootstrapping sample quantiles of strongly mixing sequences

Part of: Nonparametric inference Inference from stochastic processes

Published online by Cambridge University Press:  09 April 2009

Shuxia Sun
Shuxia Sun
Affiliation:
Department of Mathematics and Statistics Wright State University Dayton, OH 45435USA e-mail: [email protected]
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Abstract

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In this paper, we examine the rate of convergence of moving block bootstrap (MBB) approximations to the distributions of normalized sample quantiles based on strongly mixing observations. Under suitable smoothness and regularity conditions on the one-dimensional marginal distribution function, the rate of convergence of the MBB approximations to distributions of centered and scaled sample quantiles is of order O(n−1¼ log logn).

Keywords

weakly dependentstrictly stationarystrongly mixingmoving block bootstrapsample quantile.

MSC classification

Secondary: 62G09: Resampling methods 62M10: Time series, auto-correlation, regression, etc.
Type
Research Article
Information
Journal of the Australian Mathematical Society , Volume 82 , Issue 2 , April 2007 , pp. 263 - 282
Copyright
Copyright © Australian Mathematical Society 2007

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