Moment bounds for non-linear functionals of the periodogram
Abstract
In this paper, we prove the validity of the Edgeworth expansion of the Discrete Fourier transforms of some linear time series. This result is applied to approach moments of non-linear functionals of the periodogram. As an illustration, we give an expression of the mean square error of the slightly modified Geweke and Porter-Hudak estimator of the long memory parameter. We prove that this estimator is rate optimal, extending the result of Giraitis et al. (1997) [12] from Gaussian to linear processes.Download Info
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Bibliographic Info
Article provided by Elsevier in its journal Stochastic Processes and their Applications.
Volume (Year): 120 (2010)
Issue (Month): 6 (June)
Pages: 983-1009
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Related research
Keywords: Linear processes Discrete Fourier transform Periodogram Long range dependence Geweke and Porter-Hudak (GPH) estimator Log-periodogram regression;References
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