In this work we introduce a new 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. First we investigate properties of this type of bootstrap, then we apply the method to semi-parametric estimators of the long memory parameter. We find out that the performance of our bootstrap procedure is superior, in terms of MSE, to other established approaches.

A new bootstrap approach for Gaussian long memory time series.

Bordignon, Silvano;Bisaglia, Luisa;Cecchinato, Nedda
2006

Abstract

In this work we introduce a new 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. First we investigate properties of this type of bootstrap, then we apply the method to semi-parametric estimators of the long memory parameter. We find out that the performance of our bootstrap procedure is superior, in terms of MSE, to other established approaches.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11577/3442348
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