Comptes Rendus
Local block bootstrap
[Bloc re-échantillonnage local]
Comptes Rendus. Mathématique, Volume 335 (2002) no. 11, pp. 959-962.

Pour les séries chronologiques qui ne sont pas stationnaires, la méthode de bloc re-échantillonnage n'est pas directement applicable. Cependant, si la structure stochastique fondamentale change lentement, on peut utiliser une méthode de bloc re-échantillonnage local. Nous définissons une telle procédure et donnons un exemple de son applicabilité.

For time series that are not stationary, the block bootstrap method is not directly applicable. However, if the underlying stochastic structure is slowly changing with time, one may employ a local block-resampling procedure. We define such a procedure, and give an example of its applicability.

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DOI : 10.1016/S1631-073X(02)02578-5
Efstathios Paparoditis 1 ; Dimitris N. Politis 2

1 Department of Mathematics and Statistics, University of Cyprus, PO Box 20537, Nicosia, Cyprus
2 Department of Mathematics, University of California–San Diego, La Jolla, CA 92093-0112, USA
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Efstathios Paparoditis; Dimitris N. Politis. Local block bootstrap. Comptes Rendus. Mathématique, Volume 335 (2002) no. 11, pp. 959-962. doi : 10.1016/S1631-073X(02)02578-5. https://comptes-rendus.academie-sciences.fr/mathematique/articles/10.1016/S1631-073X(02)02578-5/

[1] R. Dahlhaus On the Kullback–Leibler information divergence of locally stationary processes, Stochastic Process. Appl, Volume 62 (1996), pp. 139-168

[2] R. Dahlhaus Fitting time series models to nonstationary processes, Ann. Statist, Volume 25 (1997), pp. 1-37

[3] H.R. Künsch The Jackknife and the bootstrap for general stationary observations, Ann. Statist, Volume 17 (1989), pp. 1217-1241

[4] D.N. Politis; J.P. Romano; M. Wolf Subsampling, Springer, New York, 1999

[5] M.B. Priestley Non-Linear and Non-Stationary Time Series Analysis, Academic Press, London, 1988

[6] G.G. Roussas; L.T. Tran; D.A. Ioannides Fixed design regression for time series: asymptotic normality, J. Multivariate Anal, Volume 40 (1992), pp. 262-291

[7] S.G. Shi Local bootstrap, Ann. Inst. Statist. Math, Volume 43 (1991), pp. 667-676

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