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March 2013 Canonical correlation analysis between time series and static outcomes, with application to the spectral analysis of heart rate variability
Robert T. Krafty, Martica Hall
Ann. Appl. Stat. 7(1): 570-587 (March 2013). DOI: 10.1214/12-AOAS601

Abstract

Although many studies collect biomedical time series signals from multiple subjects, there is a dearth of models and methods for assessing the association between frequency domain properties of time series and other study outcomes. This article introduces the random Cramér representation as a joint model for collections of time series and static outcomes where power spectra are random functions that are correlated with the outcomes. A canonical correlation analysis between cepstral coefficients and static outcomes is developed to provide a flexible yet interpretable measure of association. Estimates of the canonical correlations and weight functions are obtained from a canonical correlation analysis between the static outcomes and maximum Whittle likelihood estimates of truncated cepstral coefficients. The proposed methodology is used to analyze the association between the spectrum of heart rate variability and measures of sleep duration and fragmentation in a study of older adults who serve as the primary caregiver for their ill spouse.

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Robert T. Krafty. Martica Hall. "Canonical correlation analysis between time series and static outcomes, with application to the spectral analysis of heart rate variability." Ann. Appl. Stat. 7 (1) 570 - 587, March 2013. https://doi.org/10.1214/12-AOAS601

Information

Published: March 2013
First available in Project Euclid: 9 April 2013

zbMATH: 06171284
MathSciNet: MR3086431
Digital Object Identifier: 10.1214/12-AOAS601

Keywords: canonical correlation analysis , cepstral analysis , heart rate variability , sleep , spectral analysis , time series

Rights: Copyright © 2013 Institute of Mathematical Statistics

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Vol.7 • No. 1 • March 2013
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