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• W2059094041 abstract "In this work, we investigate an alternative bootstrap approach based on a result of Ramsey [F.L. Ramsey, Characterization of the partial autocorrelation function, Ann. Statist. 2 (1974), pp. 1296–1301] and on the Durbin–Levinson algorithm to obtain a surrogate series from linear Gaussian processes with long range dependence. We compare this bootstrap method with other existing procedures in a wide Monte Carlo experiment by estimating, parametrically and semi-parametrically, the memory parameter d. We consider Gaussian and non-Gaussian processes to prove the robustness of the method to deviations from normality. The approach is also useful to estimate confidence intervals for the memory parameter d by improving the coverage level of the interval." @default.
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• W2059094041 date "2010-09-01" @default.
• W2059094041 modified "2023-09-26" @default.
• W2059094041 title "Bootstrap approaches for estimation and confidence intervals of long memory processes" @default.
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• W2059094041 doi "https://doi.org/10.1080/00949650902849286" @default.
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