Spectra in low-rank localized layers (SpeLLL) for interpretable time-frequency analysis.
Spectra in low-rank localized layers (SpeLLL) for interpretable time-frequency analysis.
复制标题
低阶局部层 (SpeLLL) 中的频谱，用于可解释的时频分析。
DOI：
10.1111/biom.13577
复制
发表时间：
2023
期刊：
影响因子：
1.9
通讯作者：
Krafty,RobertT
中科院分区：
文献类型：
--
作者：
Tuft,Marie;Hall,MarticaH;Krafty,RobertT
许多生物医学时间序列的时变频率特征包含重要的科学信息。然而，时变功率谱作为时间和频率表面的高维性质限制了应用研究人员和临床医生直接使用它来阐明复杂的机制。在本文中，我们介绍了一种新的时频分析方法，该方法将时变功率谱分解为时间和频率上的正交一层，以提供一个简洁的表示，说明不同时间和频率下功率之间的关系。该方法可用于完全非参数分析或考虑外生信息和时变协变量的半参数分析。估计程序是在一个受惩罚的降秩回归框架内制定的，该框架提供了可解释为在时间块和频带内的功率局部化的层的估计。在模拟研究中说明了该程序的经验性质，并通过分析睡眠期间的心率变异性来证明其实际用途。
The time‐varying frequency characteristics of many biomedical time series contain important scientific information. However, the high‐dimensional nature of the time‐varying power spectrum as a surface in time and frequency limits its direct use by applied researchers and clinicians for elucidating complex mechanisms. In this article, we introduce a new approach to time–frequency analysis that decomposes the time‐varying power spectrum in to orthogonal rank‐one layers in time and frequency to provide a parsimonious representation that illustrates relationships between power at different times and frequencies. The approach can be used in fully nonparametric analyses or in semiparametric analyses that account for exogenous information and time‐varying covariates. An estimation procedure is formulated within a penalized reduced‐rank regression framework that provides estimates of layers that are interpretable as power localized within time blocks and frequency bands. Empirical properties of the procedure are illustrated in simulation studies and its practical use is demonstrated through an analysis of heart rate variability during sleep.