Open Access
Translator Disclaimer
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


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.


Download Citation

Dimitris N. Politis. "The Impact of Bootstrap Methods on Time Series Analysis." Statist. Sci. 18 (2) 219 - 230, May 2003.


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

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

Keywords: block bootstrap , confidence intervals , large sample inference , linear models , nonparametric estimation , Resampling , subsampling

Rights: Copyright © 2003 Institute of Mathematical Statistics


Vol.18 • No. 2 • May 2003
Back to Top