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Bootstrap in nonstationary autoregression
Kybernetika, Tome 38 (2002) no. 4, pp. 389-404 Cet article a éte moissonné depuis la source Czech Digital Mathematics Library

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The first-order autoregression model with heteroskedastic innovations is considered and it is shown that the classical bootstrap procedure based on estimated residuals fails for the least-squares estimator of the autoregression coefficient. A different procedure called wild bootstrap, respectively its modification is considered and its consistency in the strong sense is established under very mild moment conditions.
The first-order autoregression model with heteroskedastic innovations is considered and it is shown that the classical bootstrap procedure based on estimated residuals fails for the least-squares estimator of the autoregression coefficient. A different procedure called wild bootstrap, respectively its modification is considered and its consistency in the strong sense is established under very mild moment conditions.
Classification : 62F40, 62G09, 62M10 
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     zbl = {1264.62072},
     language = {en},
     url = {http://geodesic.mathdoc.fr/item/KYB_2002_38_4_a0/}
}
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Prášková, Zuzana. Bootstrap in nonstationary autoregression. Kybernetika, Tome 38 (2002) no. 4, pp. 389-404. http://geodesic.mathdoc.fr/item/KYB_2002_38_4_a0/

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