Robust coherence analysis for long-memory processes
- Authors
- Lim, Yaeji; Oh, Hee-Seok
- Issue Date
- 12-Mar-2021
- Publisher
- ROUTLEDGE JOURNALS, TAYLOR & FRANCIS LTD
- Keywords
- Cross-spectrum; Laplace cross-periodogram; long-memory process; robust coherence analysis
- Citation
- APPLIED ECONOMICS LETTERS, v.28, no.5, pp 335 - 342
- Pages
- 8
- Journal Title
- APPLIED ECONOMICS LETTERS
- Volume
- 28
- Number
- 5
- Start Page
- 335
- End Page
- 342
- URI
- https://scholarworks.bwise.kr/cau/handle/2019.sw.cau/37820
- DOI
- 10.1080/13504851.2020.1730749
- ISSN
- 1350-4851
1466-4291
- Abstract
- This paper investigates the linear relationships between two time-series in the frequency domain, termed coherence analysis. It is widely used in various fields, including signal processing, engineering, and meteorology. However, conventional coherence analysis tends to be sensitive to outliers. Laplace cross-periodogram and a corresponding robust coherence analysis based on the least-absolute deviation (LAD) regression have recently been developed to improve this shortcoming. In this paper, to extend the scope of Laplace cross-periodogram, we study a robust cross periodogram for long-memory processes and derive its asymptotic distribution. Through numerical studies, we demonstrate the usefulness of the proposed robust coherence analysis for long-memory processes.
- Files in This Item
- There are no files associated with this item.
- Appears in
Collections - Graduate School > ETC > 1. Journal Articles
Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.