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Bisaglia, Luisa and Bordignon, Silvano and Cecchinato, Nedda (2008) Bootstrap approaches for estimation and condence intervals of long memory processes. [Working Paper] WORKING PAPER SERIES, 13/2008 . , PADOVA (Inedito)

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Abstract (english)

In this work we investigate an alternative bootstrap approach based on a result of Ramsey (1974) and on the Durbin-Levinson algorithm to obtain 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 semiparametrically, 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 useful also to estimate condence intervals for the memory parameter d by improving the coverage level of the interval.

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EPrint type:Working Paper
Anno di Pubblicazione:September 2008
Key Words:bootstrap for time series, long memory, GPH and LW estimator, condence intervals.
Settori scientifico-disciplinari MIUR:Area 13 - Scienze economiche e statistiche > SECS-S/01 Statistica
Struttura di riferimento:Dipartimenti > Dipartimento di Scienze Statistiche
Codice ID:7137
Depositato il:11 Sep 2014 17:05
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