Spectrum inference for replicated spatial locally time-harmonizable time series

In this paper we develop tools for statistical inference on replicated realizations of spatiotemporal processes that are locally time-harmonizable. Our method estimates both the rescaled spatial time-varying Loève-spectrum and the spatial time-varying dual-frequency coherence function under realisti...

Full description

Saved in:
Bibliographic Details
Published inElectronic journal of statistics Vol. 17; no. 1; pp. 1371 - 1410
Main Authors Aston, John, Dehay, Dominique, Dudek, Anna E., Freyermuth, Jean-Marc, Szucs, Denes, Colling, Lincoln
Format Journal Article
LanguageEnglish
Published Shaker Heights, OH : Institute of Mathematical Statistics 01.01.2023
Subjects
Mathematics
Statistics
ElectroEncephaloGraphy
functional connectivity
Harmonizable spatiotemporal processes
nonparametric spectral analysis
Circular Block Bootstrap
Online AccessGet full text

Cover

More Information
Summary:In this paper we develop tools for statistical inference on replicated realizations of spatiotemporal processes that are locally time-harmonizable. Our method estimates both the rescaled spatial time-varying Loève-spectrum and the spatial time-varying dual-frequency coherence function under realistic modeling assumptions. We construct confidence intervals for these parameters of interest using the Circular Block Bootstrap method and prove its consistency. We illustrate the application of our methodology on a dataset arising from an experiment in neuropsychology. From EEG recordings, our method allows to study the dynamic functional connectivity within the brain associated to visual working memory performance.
ISSN:1935-7524
1935-7524
DOI:10.1214/23-EJS2130