G-Filtering Nonstationary Time Series
Joint Authors
Xu, Mengyuan
Cohlmia, Krista B.
Woodward, Wayne A.
Gray, Henry L.
Source
Journal of Probability and Statistics
Issue
Vol. 2012, Issue 2012 (31 Dec. 2012), pp.1-15, 15 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2012-03-04
Country of Publication
Egypt
No. of Pages
15
Main Subjects
Abstract EN
The classical linear filter can successfully filter the components from a time series for which the frequency content does not change with time, and those nonstationary time series with time-varying frequency (TVF) components that do not overlap.
However, for many types of nonstationary time series, the TVF components often overlap in time.
In such a situation, the classical linear filtering method fails to extract components from the original process.
In this paper, we introduce and theoretically develop the G-filter based on a time-deformation technique.
Simulation examples and a real bat echolocation example illustrate that the G-filter can successfully filter a G-stationary process whose TVF components overlap with time.
American Psychological Association (APA)
Xu, Mengyuan& Cohlmia, Krista B.& Woodward, Wayne A.& Gray, Henry L.. 2012. G-Filtering Nonstationary Time Series. Journal of Probability and Statistics،Vol. 2012, no. 2012, pp.1-15.
https://search.emarefa.net/detail/BIM-494790
Modern Language Association (MLA)
Xu, Mengyuan…[et al.]. G-Filtering Nonstationary Time Series. Journal of Probability and Statistics No. 2012 (2012), pp.1-15.
https://search.emarefa.net/detail/BIM-494790
American Medical Association (AMA)
Xu, Mengyuan& Cohlmia, Krista B.& Woodward, Wayne A.& Gray, Henry L.. G-Filtering Nonstationary Time Series. Journal of Probability and Statistics. 2012. Vol. 2012, no. 2012, pp.1-15.
https://search.emarefa.net/detail/BIM-494790
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-494790