Model order selection in periodic long memory models

Publikation: Beitrag in FachzeitschriftArtikelForschungPeer-Review

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  • Christian Leschinski
  • Philipp Sibbertsen

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OriginalspracheEnglisch
Seiten (von - bis)78-94
Seitenumfang17
FachzeitschriftEconometrics and Statistics
Jahrgang9
Frühes Online-Datum31 Jan. 2018
PublikationsstatusVeröffentlicht - Jan. 2019

Abstract

An automatic model order selection procedure for k-factor Gegenbauer processes is proposed. The procedure is based on sequential tests of the maximum of the periodogram and semiparametric estimators of the model parameters. As a byproduct, a generalized version of Walker's large sample g-test is introduced that allows to test for persistent periodicity in stationary short memory processes. Simulation studies show that the model order selection procedure performs well in identifying the correct order under various circumstances. An application to Californian electricity load data illustrates its value in empirical analyses and allows new insights into the periodicity of this process that has been the subject of several studies.

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Model order selection in periodic long memory models. / Leschinski, Christian; Sibbertsen, Philipp.
in: Econometrics and Statistics, Jahrgang 9, 01.2019, S. 78-94.

Publikation: Beitrag in FachzeitschriftArtikelForschungPeer-Review

Leschinski C, Sibbertsen P. Model order selection in periodic long memory models. Econometrics and Statistics. 2019 Jan;9:78-94. Epub 2018 Jan 31. doi: 10.1016/j.ecosta.2017.11.002, 10.1016/j.ecosta.2021.02.001
Leschinski, Christian ; Sibbertsen, Philipp. / Model order selection in periodic long memory models. in: Econometrics and Statistics. 2019 ; Jahrgang 9. S. 78-94.
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