Two-stage least squares based iterative estimation algorithm for CARARMA system modeling

作者：Ding Feng^*

来源：Applied Mathematical Modelling, 2013, 37(7): 4798-4808.

DOI：10.1016/j.apm.2012.10.014

• Least squares
• Parameter estimation
• Iterative identification
• Recursive identification

For stochastic systems described by the controlled autoregressive autoregressive moving average (CARARMA) models, a new-type two-stage least squares based iterative algorithm is proposed for identifying the system model parameters and the noise model parameters. The basic idea is based on the interactive estimation theory and to estimate the parameter vectors of the system model and the noise model, respectively. The simulation results indicate that the proposed algorithm is effective.

• 出版日期2013-4-1
• 单位江南大学