Wavelet spectral testing: application to nonstationary circadian rhythms

DOI10.1214/19-AOAS1246zbMath1433.62304arXiv1803.09507OpenAlexW2981283329MaRDI QIDQ2281228

Jack Munns, Sangeeta Chawla, Seth J. Davis, Jessica K. Hargreaves, Marina I. Knight, Rachael J. Oakenfull, Jonathan William Pitchford

Publication date: 19 December 2019

Published in: The Annals of Applied Statistics (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1803.09507

zbMATH Keywords

waveletshypothesis testingspectral decompositioncircadian rhythms

Mathematics Subject Classification ID

Computational methods for problems pertaining to statistics (62-08) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Applications of statistics to biology and medical sciences; meta analysis (62P10) Nontrigonometric harmonic analysis involving wavelets and other special systems (42C40) Inference from stochastic processes and spectral analysis (62M15) Biological rhythms and synchronization (92B25)

Related Items (5)

Wavelet testing for a replicate-effect within an ordered multiple-trial experiment ⋮ Trend locally stationary wavelet processes ⋮ A wavelet-based approach for imputation in nonstationary multivariate time series ⋮ Wavelet spectral testing: application to nonstationary circadian rhythms ⋮ Multiscale spectral modelling for nonstationary time series within an ordered multiple-trial experiment

Uses Software

• WaveThresh4
• fda (R)
• Wavos
• haarfisz
• waveclock

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