Estimation of cyclic long-memory parameters
Document type :
Article dans une revue scientifique: Article original
Permalink :
Title :
Estimation of cyclic long-memory parameters
Author(s) :
Alomari, Huda Mohammed [Auteur]
Ayache, Antoine [Auteur]
Laboratoire Paul Painlevé - UMR 8524 [LPP]
Fradon, Myriam [Auteur]
Laboratoire Paul Painlevé - UMR 8524 [LPP]
Olenko, Andriy [Auteur]
La Trobe University
Ayache, Antoine [Auteur]
Laboratoire Paul Painlevé - UMR 8524 [LPP]
Fradon, Myriam [Auteur]

Laboratoire Paul Painlevé - UMR 8524 [LPP]
Olenko, Andriy [Auteur]
La Trobe University
Journal title :
Scandinavian Journal of Statistics
Publisher :
Wiley
Publication date :
2020
ISSN :
0303-6898
English keyword(s) :
estimators of parameters
stochastic process
Gegenbauer-type spectral densities
seasonal/cyclic long memory
wavelet transformation
filter
stochastic process
Gegenbauer-type spectral densities
seasonal/cyclic long memory
wavelet transformation
filter
HAL domain(s) :
Mathématiques [math]
English abstract : [en]
This paper studies cyclic long-memory processes with Gegenbauer- type spectral densities. For a semiparametric statistical model new simultaneous estimates for singularity location and long- memory parameters are proposed. ...
Show more >This paper studies cyclic long-memory processes with Gegenbauer- type spectral densities. For a semiparametric statistical model new simultaneous estimates for singularity location and long- memory parameters are proposed. This generalized filtered method of moments approach is based on general filter transforms that include wavelet transformations as a particular case. It is proved that the estimates are almost surely convergent to the true values of parameters. Solutions of the estimation equations are studied and adjusted statistics are proposed. Monte-Carlo study results are presented to confirm the theoretical findings.Show less >
Show more >This paper studies cyclic long-memory processes with Gegenbauer- type spectral densities. For a semiparametric statistical model new simultaneous estimates for singularity location and long- memory parameters are proposed. This generalized filtered method of moments approach is based on general filter transforms that include wavelet transformations as a particular case. It is proved that the estimates are almost surely convergent to the true values of parameters. Solutions of the estimation equations are studied and adjusted statistics are proposed. Monte-Carlo study results are presented to confirm the theoretical findings.Show less >
Language :
Anglais
Peer reviewed article :
Oui
Audience :
Internationale
Popular science :
Non
Collections :
Source :
Submission date :
2025-01-24T14:53:29Z