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The Impact of Bootstrap Methods on Time Series Analysis
Dimitris N. Politis
Vol. 18, No. 2, Silver Anniversary of the Bootstrap (May, 2003), pp. 219-230
Published by: Institute of Mathematical Statistics
Stable URL: http://www.jstor.org/stable/3182852
Page Count: 12
You can always find the topics here!Topics: Statism, Time series, Statistical estimation, Estimators, Estimate reliability, Bootstrap resampling, Sample mean, Statistical variance, Time series models, Time series analysis
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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.
Statistical Science © 2003 Institute of Mathematical Statistics