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The Impact of Bootstrap Methods on Time Series Analysis

2003; Institute of Mathematical Statistics; Volume: 18; Issue: 2 Linguagem: Inglês

10.1214/ss/1063994977

2168-8745

Dimitris N. Politis,

Advanced Statistical Methods and Models

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.