Gaussian semiparametric estimation in seasonal/cyclical long memory time series

Josu Arteche

Kybernetika (2000)

  • Volume: 36, Issue: 3, page [279]-310
  • ISSN: 0023-5954

Abstract

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Gaussian semiparametric or local Whittle estimation of the memory parameter in standard long memory processes was proposed by Robinson [18]. This technique shows several advantages over the popular log- periodogram regression introduced by Geweke and Porter–Hudak [7]. In particular under milder assumptions than those needed in the log periodogram regression it is asymptotically more efficient. We analyse the asymptotic behaviour of the Gaussian semiparametric estimate of the memory parameter in seasonal or cyclical long memory processes allowing for asymmetric spectral divergences or zeros. Consistency and asymptotic normality are obtained.

How to cite

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Arteche, Josu. "Gaussian semiparametric estimation in seasonal/cyclical long memory time series." Kybernetika 36.3 (2000): [279]-310. <http://eudml.org/doc/33484>.

@article{Arteche2000,
abstract = {Gaussian semiparametric or local Whittle estimation of the memory parameter in standard long memory processes was proposed by Robinson [18]. This technique shows several advantages over the popular log- periodogram regression introduced by Geweke and Porter–Hudak [7]. In particular under milder assumptions than those needed in the log periodogram regression it is asymptotically more efficient. We analyse the asymptotic behaviour of the Gaussian semiparametric estimate of the memory parameter in seasonal or cyclical long memory processes allowing for asymmetric spectral divergences or zeros. Consistency and asymptotic normality are obtained.},
author = {Arteche, Josu},
journal = {Kybernetika},
language = {eng},
number = {3},
pages = {[279]-310},
publisher = {Institute of Information Theory and Automation AS CR},
title = {Gaussian semiparametric estimation in seasonal/cyclical long memory time series},
url = {http://eudml.org/doc/33484},
volume = {36},
year = {2000},
}

TY - JOUR
AU - Arteche, Josu
TI - Gaussian semiparametric estimation in seasonal/cyclical long memory time series
JO - Kybernetika
PY - 2000
PB - Institute of Information Theory and Automation AS CR
VL - 36
IS - 3
SP - [279]
EP - 310
AB - Gaussian semiparametric or local Whittle estimation of the memory parameter in standard long memory processes was proposed by Robinson [18]. This technique shows several advantages over the popular log- periodogram regression introduced by Geweke and Porter–Hudak [7]. In particular under milder assumptions than those needed in the log periodogram regression it is asymptotically more efficient. We analyse the asymptotic behaviour of the Gaussian semiparametric estimate of the memory parameter in seasonal or cyclical long memory processes allowing for asymmetric spectral divergences or zeros. Consistency and asymptotic normality are obtained.
LA - eng
UR - http://eudml.org/doc/33484
ER -

References

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