Trend Locally Stationary Wavelet Processes

McGonigle, Euan and Killick, Rebecca and Nunes, Matthew (2022) Trend Locally Stationary Wavelet Processes. Journal of Time Series Analysis, 43 (6). pp. 895-917. ISSN 0143-9782

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Abstract

Most time series observed in practice exhibit first as well as second-order nonstationarity. In this article we propose a novel framework for modelling series with simultaneous time-varying first and second-order structure, removing the restrictive zero-mean assumption of locally stationary wavelet processes and extending the applicability of the locally stationary wavelet model to include trend components. We develop an associated estimation theory for both first and second order time series quantities and show that our estimators achieve good properties in isolation of each other by making appropriate assumptions on the series trend. We demonstrate the utility of the method by analysing the global mean sea temperature time series, highlighting the impact of the changing climate.

Item Type:
Journal Article
Journal or Publication Title:
Journal of Time Series Analysis
Uncontrolled Keywords:
/dk/atira/pure/subjectarea/asjc/2600/2613
Subjects:
?? climate datalocally stationarynon-stationary time seriestrend estimationwavelet spectrumstatistics and probabilitystatistics, probability and uncertaintygeneral agricultural and biological sciencesapplied mathematicsgeneral mathematicsagricultural and bio ??
ID Code:
167473
Deposited By:
Deposited On:
18 Mar 2022 15:40
Refereed?:
Yes
Published?:
Published
Last Modified:
09 Oct 2024 11:06