Analysis of Nonstationary Time Series for Biological Rhythms Research

被引:31
|
作者
Leise, Tanya L. [1 ]
机构
[1] Amherst Coll, Dept Math & Stat, Amherst, MA 01002 USA
关键词
time-frequency analysis; wavelet transform; biological rhythms; mathematical analyses; circadian rhythms; ROBUSTNESS; STATISTICS; TRANSFORM; SIGNAL; SLEEP;
D O I
10.1177/0748730417709105
中图分类号
Q [生物科学];
学科分类号
07 ; 0710 ; 09 ;
摘要
This article is part of a Journal of Biological Rhythms series exploring analysis and statistics topics relevant to researchers in biological rhythms and sleep research. The goal is to provide an overview of the most common issues that arise in the analysis and interpretation of data in these fields. In this article on time series analysis for biological rhythms, we describe some methods for assessing the rhythmic properties of time series, including tests of whether a time series is indeed rhythmic. Because biological rhythms can exhibit significant fluctuations in their period, phase, and amplitude, their analysis may require methods appropriate for nonstationary time series, such as wavelet transforms, which can measure how these rhythmic parameters change over time. We illustrate these methods using simulated and real time series.
引用
收藏
页码:187 / 194
页数:8
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