Maximum likelihood recursive least squares estimation for multivariate equation-error ARMA systems

作者：Liu, Lijuan; Wang, Yan^*; Wang, Cheng; Ding, Feng^*; Hayat, Tasawar

来源：Journal of the Franklin Institute, 2018, 355(15): 7609-7625.

DOI：10.1016/j.jfranklin.2018.07.041

• PARAMETER-ESTIMATION ALGORITHM
• THRESHOLD DIVIDEND STRATEGY
• MOVING AVERAGE NOISE
• IDENTIFICATION ALGORITHMS
• DYNAMICAL-SYSTEMS
• MULTI-INNOVATION
• MODEL
• PERFORMANCE
• JUMP

This paper focuses on the parameter estimation problems of multivariate equation-error systems. A recursive generalized extended least squares algorithm is presented as a comparison. Based on the maximum likelihood principle and the coupling identification concept, the multivariate equation-error system is decomposed into several regressive identification models, each of which has only a parameter vector, and a coupled subsystem maximum likelihood recursive least squares identification algorithm is developed for estimating the parameter vectors of these submodels. The simulation example shows that the proposed algorithm is effective and has high estimation accuracy.

• 出版日期2018-10
• 单位江南大学; 青岛科技大学