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Wild bootstrap in RCA(1) model
Kybernetika, Tome 39 (2003) no. 1, pp. 1-12 Cet article a éte moissonné depuis la source Czech Digital Mathematics Library

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In the paper, a heteroskedastic autoregressive process of the first order is considered where the autoregressive parameter is random and errors are allowed to be non-identically distributed. Wild bootstrap procedure to approximate the distribution of the least-squares estimator of the mean of the random parameter is proposed as an alternative to the approximation based on asymptotic normality, and consistency of this procedure is established.
In the paper, a heteroskedastic autoregressive process of the first order is considered where the autoregressive parameter is random and errors are allowed to be non-identically distributed. Wild bootstrap procedure to approximate the distribution of the least-squares estimator of the mean of the random parameter is proposed as an alternative to the approximation based on asymptotic normality, and consistency of this procedure is established.
Classification : 62E20, 62G09, 62M10
Keywords: randomcoefficient autoregression; heteroskedasticity; wild bootstrap 
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     title = {Wild bootstrap in {RCA(1)} model},
     journal = {Kybernetika},
     pages = {1--12},
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     language = {en},
     url = {http://geodesic.mathdoc.fr/item/KYB_2003_39_1_a0/}
}
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Prášková, Zuzana. Wild bootstrap in RCA(1) model. Kybernetika, Tome 39 (2003) no. 1, pp. 1-12. http://geodesic.mathdoc.fr/item/KYB_2003_39_1_a0/

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