Displaying similar documents to “A contribution to bootstrapping autoregressive processes”

Estimation of variances in a heteroscedastic RCA(1) model

Hana Janečková (2002)

Kybernetika

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The paper concerns with a heteroscedastic random coefficient autoregressive model (RCA) of the form X t = b t X t - 1 + Y t . Two different procedures for estimating σ t 2 = E Y t 2 , σ b 2 = E b t 2 or σ B 2 = E ( b t - E b t ) 2 , respectively, are described under the special seasonal behaviour of σ t 2 . For both types of estimators strong consistency and asymptotic normality are proved.

Wild bootstrap in RCA(1) model

Zuzana Prášková (2003)

Kybernetika

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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.

Bootstrap in nonstationary autoregression

Zuzana Prášková (2002)

Kybernetika

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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.