Model-free Bootstrap for a General Class of Stationary Time Series

Dimitris N. Politis; Yiren Wang

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Model-free Bootstrap for a General Class of Stationary Time Series

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arxiv 1912.13185 v1 pith:GOY6E3TH submitted 2019-12-31 math.ST stat.TH

Yiren Wang , Dimitris N. Politis This is my paper · ORCID

classification math.STstat.TH

keywords bootstrapasymptoticclassgeneralintervalsmodel-freeseriesstationary

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A model-free bootstrap procedure for a general class of stationary time series is introduced. The theoretical framework is established, showing asymptotic validity of bootstrap confidence intervals for many statistics of interest. In addition, asymptotic validity of one-step ahead bootstrap prediction intervals is also demonstrated. Finite-sample experiments are conducted to empirically confirm the performance of the new method, and to compare with popular methods such as the block bootstrap and the autoregressive (AR)-sieve bootstrap.

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