Cosine-based variable bandwidth selection for nonparametric spectral density estimation under long-range dependence
- Authors
- Jeong, Donghoon; Young Min Kim; JONGHO IM
- Issue Date
- Mar-2022
- Publisher
- TAYLOR & FRANCIS LTD
- Keywords
- cosine-based bandwidth selection; kernel-based density estimator; long-range dependence; spectral density function; variable bandwidth
- Citation
- JOURNAL OF STATISTICAL COMPUTATION AND SIMULATION, v.92, no.6, pp 1,158 - 1,174
- Journal Title
- JOURNAL OF STATISTICAL COMPUTATION AND SIMULATION
- Volume
- 92
- Number
- 6
- Start Page
- 1,158
- End Page
- 1,174
- URI
- https://yscholarhub.yonsei.ac.kr/handle/2021.sw.yonsei/6784
- DOI
- 10.1080/00949655.2021.1988947
- ISSN
- 0094-9655
- Abstract
- The optimal bandwidth selection in kernel-based nonparametric density estimation is one of the important parts in the spectral density estimation under long-range dependence (LRD). To improve the performance of the nonparametric spectral density estimation (NPSDE) under LRD, we propose a new cosine-based variable bandwidth selection method, which is motivated by variable bandwidth selection for density estimation and spectral density for autoregressive fractionally-integrated moving average models. The performance of the proposed method was illustrated through the simulation studies and data examples. The proposed cosine-based variable bandwidth selection method for NPSDE under LRD provides better performance than any other bandwidth selection method. Our method is robust to any values of the fractional differencing parameters.
- Files in This Item
- There are no files associated with this item.
- Appears in
Collections - College of Commerce and Economics > Applied Statistics > 1. Journal Articles
Items in Scholar Hub are protected by copyright, with all rights reserved, unless otherwise indicated.