一阶广义随机系数自回归模型参数的最小渐近方差估计

Smallest Asymptotic Variance Estimator for Generalized Random Coefficient Autoregressive Model

研究广义随机系数自回归模型中参数的估计问题,给出了未知参数的一个估计类,证明了该估计类中估计的相合性和渐近正态性,并且获得了该估计类中的最小渐近方差估计,并通过数值模拟比较了估计类中各种估计方法的优劣.

The parameter estimator of generalized random coefficient autoregressive model was studied and a class of estimators of unknown parameter was presented. We proved the consistency and the asymptotic normality of the estimators among the class of estimators and obtained the smallest asymptotic variance estimator. Furthermore, some simulation studies were conducted to investigate the finite performances of the proposed estimators.