Asymptotic efficiency of the OLSE for polynomial regression models with spatially correlated errors

作     者：Shin, DW Song, SH 

作者机构：Ewha Univ Dept Stat Seodaemun Ku Seoul 120750 South Korea Duksung Univ Dept Stat Tobong Ku Seoul 132714 South Korea 

出 版 物：《STATISTICS & PROBABILITY LETTERS》 (统计学与概率论通讯)

年 卷 期：2000年第47卷第1期

页      面：1-10页

核心收录：

学科分类：07[理学] 0714[理学-统计学（可授理学、经济学学位）] 0701[理学-数学] 070101[理学-基础数学] 

基　　金：Korea Science and Engineering Foundation  KOSEF 

主　　题：polynomial regression model spatial correlation efficiency OLSE GLSE 

摘      要：For polynomial regression models with spatially correlated errors, the covariance matrix of the ordinary least-squares estimator (OLSE) is shown to have the same limiting value as that of the generalized least-squares estimator (GLSE) under the same normalization. This implies that the OLSE is asymptotically efficient. (C) 2000 Elsevier Science B.V. All rights reserved.