Matrix-variate time series modelling with hidden Markov models

作     者：Asilkalkan, Abdullah Zhu, Xuwen 

作者机构：Univ Alabama Dept Informat Syst Stat & Management Sci Tuscaloosa AL 35487 USA 

出 版 物：《STAT》 (Stat)

年 卷 期：2021年第10卷第1期

核心收录：

主　　题：EM algorithm hidden Markov model matrix normal distribution time series 

摘      要：In this paper, a hidden Markov model for modelling matrix-variate time series data is developed. It relies on matrix-variate distribution and presents a promising alternative to the existing methods. Simulation study is carefully conducted and uses benchmark tests with pre-specified overlapping values. Compared with the existing methods, the proposed model demonstrates rather high accuracy in state classification. Results suggest that such an approach is indeed competitive. Interesting applications are presented for real-life data illustration.