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Activity Number:
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369
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Type:
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Contributed
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Date/Time:
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Tuesday, August 4, 2009 : 2:00 PM to 3:50 PM
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Sponsor:
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Section on Nonparametric Statistics
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| Abstract - #304437 |
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Title:
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On Confidence Intervals for the Mean of a Long-Range Dependent Process
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Author(s):
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Zhewen Fan*+ and Xiaofeng Shao
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Companies:
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University of Illinois at Urbana-Champaign and University of Illinois at Urbana-Champaign
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Address:
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725 S. Wright Street, Champaign, IL, 61820,
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Keywords:
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Long-range dependence ; Subsampling ; Functional central limit theorem
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Abstract:
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The paper is concerned with confidence interval construction of the mean for a stationary long-range dependent process. We focus on two classes of processes: transformation of Gaussian processes and linear processes. Hall, Jing and Lahiri (Statistica Sinica,1998) proposed a subsampling method that involves an estimation of the variance of the normalized sample mean using two seemingly arbitrary tuning parameters. To eliminate the need for variance estimation, we first form a self-normalized statistic, whose asymptotic distribution is free of the asymptotic variance of the sample mean, then apply the subsampling method. The proposed method is compared to Hall et al's through simulation studies.
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