Linear estimation of the regression model with ARMA disturbances: A simulation study

被引：1

作者：

Choudhury, AH

Power, S

StLouis, RD

机构：

[1] UNIV ALASKA,SCH BUSINESS,ANCHORAGE,AK 99508

[2] CARLETON UNIV,DEPT ECON,OTTAWA,ON K1S 5B6,CANADA

[3] ARIZONA STATE UNIV,COLL BUSINESS,TEMPE,AZ 85287

来源：

COMMUNICATIONS IN STATISTICS-SIMULATION AND COMPUTATION | 1997年 / 26卷 / 01期

关键词：

regression; autocorrelation; approximate GLS estimator;

D O I：

10.1080/03610919708813382

中图分类号：

O21 [概率论与数理统计]; C8 [统计学];

学科分类号：

020208 ; 070103 ; 0714 ;

摘要：

Koreisha and Pukkila (1990a) have recently proposed a computationally convenient three-step GLS-type linear estimator for the regression model with ARMA disturbances involving three sequential applications of least squares. One potential drawback to this estimation procedure is that it entails dropping a significant number of initial observations. This paper uses Monte Carlo methods to evaluate its performance vis-a-vis existing OLS and GLS linear estimators.

引用

页码：315 / 332

页数：18

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