Open Access Open Access  Restricted Access Subscription or Fee Access

On block bootstrapping for autoregressive time series models

Beste H. Beyazta, Ufuk Beyaztas


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.


bootstrap; ordinary least squares; simulation; time series.

Full Text:


Disclaimer/Regarding indexing issue:

We have provided the online access of all issues and papers to the indexing agencies (as given on journal web site). It’s depend on indexing agencies when, how and what manner they can index or not. Hence, we like to inform that on the basis of earlier indexing, we can’t predict the today or future indexing policy of third party (i.e. indexing agencies) as they have right to discontinue any journal at any time without prior information to the journal. So, please neither sends any question nor expects any answer from us on the behalf of third party i.e. indexing agencies.Hence, we will not issue any certificate or letter for indexing issue. Our role is just to provide the online access to them. So we do properly this and one can visit indexing agencies website to get the authentic information.