Bootstrap approaches for estimation and confidence intervals of long term memory processes
Bisaglia, Luisa, Bordignon, Silvano, & Cecchinato, Nedda (2009) Bootstrap approaches for estimation and confidence intervals of long term memory processes. Journal of Statistical Computation and Simulation.
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.
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|Item Type:||Journal Article|
|Keywords:||Bootstrap for time series, Long memory, GPH and LW estimator, Confidence intervals|
|Subjects:||Australian and New Zealand Standard Research Classification > ECONOMICS (140000) > OTHER ECONOMICS (149900) > Economics not elsewhere classified (149999)
Australian and New Zealand Standard Research Classification > ECONOMICS (140000) > ECONOMETRICS (140300) > Time-Series Analysis (140305)
|Divisions:||Current > QUT Faculties and Divisions > QUT Business School
Current > Schools > School of Economics & Finance
|Copyright Owner:||Copyright 2009 Taylor & Francis|
|Deposited On:||23 May 2010 22:29|
|Last Modified:||29 Feb 2012 13:56|
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