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May 2003 The Impact of Bootstrap Methods on Time Series Analysis
Dimitris N. Politis
Statist. Sci. 18(2): 219-230 (May 2003). DOI: 10.1214/ss/1063994977

Abstract

Sparked by Efron's seminal paper, the decade of the 1980s was a period of active research on bootstrap methods for independent data--mainly i.i.d. or regression set-ups. By contrast, in the 1990s much research was directed towards resampling dependent data, for example, time series and random fields. Consequently, the availability of valid nonparametric inference procedures based on resampling and/or subsampling has freed practitioners from the necessity of resorting to simplifying assumptions such as normality or linearity that may be misleading.

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Dimitris N. Politis. "The Impact of Bootstrap Methods on Time Series Analysis." Statist. Sci. 18 (2) 219 - 230, May 2003. https://doi.org/10.1214/ss/1063994977

Information

Published: May 2003
First available in Project Euclid: 19 September 2003

zbMATH: 1332.62340
MathSciNet: MR2026081
Digital Object Identifier: 10.1214/ss/1063994977

Rights: Copyright © 2003 Institute of Mathematical Statistics

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Vol.18 • No. 2 • May 2003
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