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Please use this identifier to cite or link to this item: http://hdl.handle.net/10016/4553

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ws981811.pdf-- 2009-06-30 -- Available on Internet -- preprint1,23 MBUnknown
Title: Non-Gaussian log-periodogram regression
Author(s): Velasco, Carlos [cavelas]
Publisher: Universidad Carlos III de Madrid. Departamento de Estadística
Issued date: Feb-1998
URI: http://hdl.handle.net/10016/4553
Abstract: We show the consistency of the log-periodogram estimate of the long memory parameter íor long range dependent linear, non necessarily Gaussian, time series when we make a pooling oí periodogram ordinates. Then, we study the asymptotic behaviour oí the tapered periodogram of long range dependent time series íor írequencies near the origin. Finally, we obtain the asymptotic distribution of the log-periodogram estimate íor possibly non-Gaussian observations when we use the tapered periodogram. For that result we rely on higher order asymptotic properties of a vector of periodogram ordinates of the linear innovations.
Serie / Nº.: UC3M Working Papers. Statistics and Econometrics
1998-18-11
Keywords: Long range dependence
Semiparametric iníerence
Higher order asymptotics
Tapering
Appears in Collections:DES - Working Papers. Statistics and Econometrics. WS
Economists Online

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