THE MEAN SQUARED ERROR OF THE GENERALIZED RIDGE-REGRESSION ESTIMATOR AND THE ORIENTATION OF BETA

被引：1

作者：

PLISKIN, JL ^{[1
]}

机构：

[1] HAMILTON COLL,DEPT ECON,CLINTON,NY 13323

来源：

COMMUNICATIONS IN STATISTICS-SIMULATION AND COMPUTATION | 1990年 / 19卷 / 04期

关键词：

BIASED ESTIMATION; MONTE-CARLO EXPERIMENT; LINEAR REGRESSION MODEL; PREDICTION; MULTICOLLINEARITY;

D O I：

10.1080/03610919008812930

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：

Newhouse and Oman (1971) identified the orientations with respect to the eigenvectors of X'X of the true coefficient vector of the linear regression model for which the ordinary ridge regression estimator performs best and performs worse when mean squared error is the measure of performance. In this paper the corresponding result is derived for generalized ridge regression for two risk functions: mean squared error and mean squared error of prediction.

引用

页码：1477 / 1484

页数：8

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