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Asymptotic normality of simultaneous estimators of cyclic long-memory processes

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journal contribution
posted on 20.05.2022, 04:46 authored by A Ayache, M Fradon, Ravindi NanayakkaraRavindi Nanayakkara, Andriy OlenkoAndriy Olenko
Spectral singularities at non-zero frequencies play an impor-tant role in investigating cyclic or seasonal time series. The publication [2] introduced the generalized filtered method-of-moments approach to simul-taneously estimate singularity location and long-memory parameters. This paper continues studies of these simultaneous estimators. A wide class of Gegenbauer-type semi-parametric models is considered. Asymptotic normality of several statistics of the cyclic and long-memory parameters is proved. New adjusted estimates are proposed and investigated. The theoretical findings are illustrated by numerical results. The methodology in-cludes wavelet transformations as a particular case.

Funding

Ravindi Nanayakkara and Andriy Olenko were partially supported under the Australian Research Council's Discovery Projects funding scheme (project DP160101366).

History

Publication Date

01/01/2022

Journal

Electronic Journal of Statistics

Volume

16

Issue

1

Pagination

(p. 84-115)

Publisher

Institute of Mathematical Statistics (IMS)

ISSN

1935-7524

Rights Statement

© The Author(s) 2022. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made.