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August 1997 Note on convergence rates of semiparametric estimators of dependence index
Peter Hall, Hira L. Koul, Berwin A. Turlach
Ann. Statist. 25(4): 1725-1739 (August 1997). DOI: 10.1214/aos/1031594739

Abstract

Considerable recent attention has been devoted to semiparametric estimation of the dependence index, or the Hurst constant, using methods based on information in either frequency or time domains. Convergence rates of estimators in the frequency domain have been derived, and in the present paper we obtain them for estimators in the time domain. It is shown that the latter can have superior performance for moderate-range time series, but are inferior in the context of long-range dependence.

Citation

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Peter Hall. Hira L. Koul. Berwin A. Turlach. "Note on convergence rates of semiparametric estimators of dependence index." Ann. Statist. 25 (4) 1725 - 1739, August 1997. https://doi.org/10.1214/aos/1031594739

Information

Published: August 1997
First available in Project Euclid: 9 September 2002

zbMATH: 0890.62068
MathSciNet: MR1463572
Digital Object Identifier: 10.1214/aos/1031594739

Subjects:
Primary: 62M10
Secondary: 62G05

Keywords: autocovariance , Gaussian process , Hurst constant , Long-memory time series , long-range dependence , semiparametric inference , short-range dependence , stationary process

Rights: Copyright © 1997 Institute of Mathematical Statistics

Vol.25 • No. 4 • August 1997
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