G-Filtering Nonstationary Time Series

Mengyuan Xu, Krista B. Cohlmia, Wayne A. Woodward and Henry L. Gray

Journal of Probability and Statistics, 2012, vol. 2012, 1-15

Abstract:

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.

Date: 2012
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Persistent link: https://EconPapers.repec.org/RePEc:hin:jnljps:738636

DOI: 10.1155/2012/738636

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