Two-Stage Least Squares based Iterative Identification Algorithm for Box-Jenkins Model

Authors

Jie Jia, Institute of Aerospace Information and Security Technology, Nanchang Hangkong University, Nanchang 330063, China
Hua Huang
Yong Yang
Ke Lv
Feng Ding

Author Country (or Countries)

China

Abstract

In order to improve the parameters estimation precision, a two-stage least squares iterative algorithm for Box-Jenkins models is presented, which is based on the interactive estimation theory of the hierarchical identification and the auxiliary model. The main idea of the algorithm is to decompose a Box-Jenkins system into two subsystems so as to identify each subsystem, respectively. In our algorithm, the dimensions of the involved covariance matrices in each subsystem turn to be small. The simulation results indicate that the proposed algorithm is effective and has a high computational efficiency.

Suggested Reviewers

N/A

Digital Object Identifier (DOI)

http://dx.doi.org/10.12785/amis/080352

Recommended Citation

Jia, Jie; Huang, Hua; Yang, Yong; Lv, Ke; and Ding, Feng (2014) "Two-Stage Least Squares based Iterative Identification Algorithm for Box-Jenkins Model," Applied Mathematics & Information Sciences: Vol. 08: Iss. 3, Article 52.
DOI: http://dx.doi.org/10.12785/amis/080352
Available at: https://digitalcommons.aaru.edu.jo/amis/vol08/iss3/52