NEAR (p) 模型的参数估计

NEAR (p) 模型的参数估计

朱复康¹, 王德辉¹，曹伟²

1. 吉林大学数学研究所, 长春 130012; 2. 吉林大学哲学社会学院，长春 130012

收稿日期:2005-12-09 修回日期:1900-01-01 出版日期:2006-11-26 发布日期:2006-08-26
通讯作者: 王德辉

Parameter Estimation for the NEAR(p) Model

ZHU Fukang¹, WANG Dehui¹, CAO Wei²

1. Institute of Mathematics, Jilin University, Changchun 130012, China;2. College of Philosophy Sociology, Jilin University, Changchun 130012, China

Received:2005-12-09 Revised:1900-01-01 Online:2006-11-26 Published:2006-08-26
Contact: WANG Dehui

摘要/Abstract

摘要： 分别用条件最小二乘、加权条件最小二乘和最大拟似然方法估计了平稳的NEAR(p)模型的参数. 并讨论了这些估计量的渐近性质. 通过数值模拟发现, 当参数真值较小时, 最大拟似然方法的估计效果较好；当参数真值较大时, 加权条件最小二乘方法的估计效果较好.

关键词: NEAR(p)模型, 条件最小二乘估计, 加权条件最小二乘估计, 最大拟似然估计

Abstract: The parameters of a stationary NEAR(p) (new exponential autoregressive process of order p) model were estimated by means of conditional least squares, weighted conditional least squares and maximum quasi likelihood approach, respectively. For those estimators, we discussed their asymptotic properties and showed via simulation that maximum quasilikelihood es timation dominates the others when the true values of the parameters are small, while weighted conditional least squares estimation dominates the others when the true values of the parameters are big.

Key words: NEAR(p) model, conditional least squares estimati on, weighted conditional least squares estimation, maximum quasilikelihood est imation

中图分类号:

O212.1

朱复康, 王德辉，曹伟. NEAR (p) 模型的参数估计[J]. J4, 2006, 44(06): 851-856.

ZHU Fukang, WANG Dehui, CAO Wei. Parameter Estimation for the NEAR(p) Model[J]. J4, 2006, 44(06): 851-856.