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Asymptotic normality of simultaneous estimators of cyclic long-memory processes
journal contributionposted on 2022-05-20, 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  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.
Ravindi Nanayakkara and Andriy Olenko were partially supported under the Australian Research Council's Discovery Projects funding scheme (project DP160101366).
JournalElectronic Journal of Statistics
PublisherInstitute of Mathematical Statistics (IMS)
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.