A note on the properties of Stein-rule and inequality restricted estimators when the regression model is over-fitted
被引:0
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作者:
Zhou, Sherry Zhefang
论文数: 0引用数: 0
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机构:
City Univ Hong Kong, Dept Management Sci, Kowloon, Hong Kong, Peoples R ChinaCity Univ Hong Kong, Dept Management Sci, Kowloon, Hong Kong, Peoples R China
Zhou, Sherry Zhefang
[1
]
机构:
[1] City Univ Hong Kong, Dept Management Sci, Kowloon, Hong Kong, Peoples R China
Inequality restricted estimator;
linear regression model;
model misspecification;
stein-rule estimator;
LEAST-SQUARES;
LINEAR-REGRESSION;
ERROR;
MISSPECIFICATION;
SENSITIVITY;
VARIANCE;
MATRIX;
OLS;
D O I:
10.1007/s11424-010-9087-4
中图分类号:
O1 [数学];
学科分类号:
0701 ;
070101 ;
摘要:
This paper considers the effect of an erroneous inclusion of regressors on the risk properties of the Stein-rule, positive-part Stein-rule and inequality restricted and pre-test estimators in a linear regression model. The two Stein-rule estimators are considered when extraneous information is available in the form of a set of multiple equality constraints on the coefficients, while the inequality estimators are considered under the case of a single inequality constraint. It is shown that the inclusion of wrong regressors has only minimal effect on the properties of the Stein-rule and positive-part Stein-rule estimators, and no effect at all on the inequality restricted and pre-test estimators when there is a single inequality constraint.