| Citation: | HAN Yu, TIAN Baocheng, WANG Shupenget al. A combined estimation functions method for autoregressive model with time-varying variance[J]. Journal of Beijing University of Aeronautics and Astronautics, 2022, 48(5): 756-761. doi: 10.13700/j.bh.1001-5965.2020.0657(in Chinese)
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With regard to the problem of parameter estimation, the combined estimation functions method is used to carry out statistical research on the parameter of autoregressive model with time-varying variance. The research status of the autoregressive model with time-varying variance and the combined estimation functions theory is reported. The combined estimation functions theory is used to obtain the parameter estimators of the autoregressive model with time-varying variance, and it is proved that the parameter estimators of the combined estimation functions method asymptotically converge to normal distribution. The numerical simulation is carried out for the comparative analysis of the proposed parameters. The simulation results show that, compared with the quasi maximum likelihood estimators and the least squares estimators, the proposed parameter estimators of combined estimation functions are slightly better than those of quasi maximum likelihood estimation, and the statistic is less affected by the distribution function of error terms.
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