文献类型：期刊文献

英文题名：Triadic time series motifs

作者：Xie, Wen-Jie[1,2]; Han, Rui-Qi[3]; Zhou, Wei-Xing[1,2,3]

机构：[1] Department of Finance, East China University of Science and Technology, Shanghai, 200237, China; [2] Research Center for Econophysics, East China University of Science and Technology, Shanghai, 200237, China; [3] Department of Mathematics, East China University of Science and Technology, Shanghai, 200237, China

年份：2018

外文期刊名：arXiv

收录：EI(收录号：20200246229)

语种：英文

外文关键词：Cardiology - Gaussian noise (electronic) - Time series analysis

摘要：We introduce the concept of time series motifs for time series analysis. Time series motifs consider not only the spatial information of mutual visibility but also the temporal infor-mation of relative magnitude between the data points. We study the profiles of the six triadic time series. The six motif occurrence frequencies are derived for uncorrelated time series, which are approximately linear functions of the length of the time series. The corresponding motif profile thus converges to a constant vector (0.2, 0.2, 0.1, 0.2, 0.1, 0.2). These analytical results have been verified by numerical simulations. For fractional Gaussian noises, numerical simulations unveil the nonlinear dependence of motif occurrence frequencies on the Hurst exponent. Applications of the time series motif analysis uncover that the motif occurrence frequency distributions are able to capture the different dynamics in the heartbeat rates of healthy subjects, congestive heart failure (CHF) subjects, and atrial fibrillation (AF) subjects and in the price fluctuations of bullish and bearish markets. Our method shows its potential power to classify different types of time series and test the time irreversibility of time series. Copyright ? 2018, The Authors. All rights reserved.