J4 ›› 2012, Vol. 50 ›› Issue (06): 1135-1140.

• 数学 • 上一篇    下一篇

一阶广义随机系数自回归模型参数的最小渐近方差估计

赵志文1, 王德辉2   

  1. 1. 吉林师范大学 数学学院, 吉林 四平 136000|2. 吉林大学 数学学院, |长春 130012
  • 收稿日期:2012-02-02 出版日期:2012-11-26 发布日期:2012-11-26
  • 通讯作者: 王德辉 E-mail:Wangdehui69@163.com

Smallest Asymptotic Variance Estimator for GeneralizedRandom Coefficient Autoregressive Model

ZHAO Zhiwen1, WANG Dehui2   

  1. 1. College of Mathematics, Jilin Normal University, Siping 136000, Jilin Province, China;2. College of Mathematics, Jilin University, Changchun 130012, China
  • Received:2012-02-02 Online:2012-11-26 Published:2012-11-26
  • Contact: WANG Dehui E-mail:Wangdehui69@163.com

摘要:

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.

关键词: 广义随机系数自回归模型, 最小二乘估计, 渐近正态性, 加权最小二乘估计, 最小渐近方差估计

Abstract:

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.

Key words: generalized random coefficient autoregressive model, least squares estimator, asymptotic normality, weighted conditional least squares estimator, smallest asymptotic variance estimator

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