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On block bootstrapping for autoregressive time series models

Beste H. Beyazta, Ufuk Beyaztas

Abstract



In this paper, we propose new Ordinary Least Squares based overlapping and non-overlapping block bootstrap methods for autoregressive time series models. The finite sample properties of the proposed methods are illustrated by an extensive simulation study and two realworld examples. Our findings reveal that the proposed methods have better performances than their conventional counterparts.

Keywords


bootstrap; ordinary least squares; simulation; time series.

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