Linear plus quadratic (LPQ) quasiminimax estimation in the linear regression model

被引：0

作者：

Knautz, H ^{[1
]}

机构：

[1] UNIV HAMBURG, INST STAT & ECONOMETR, D-20146 HAMBURG, GERMANY

来源：

ACTA APPLICANDAE MATHEMATICAE | 1996年 / 43卷 / 01期

关键词：

linear regression model; minimax estimation linear plus quadratic estimator;

D O I：

10.1007/BF00046991

中图分类号：

O29 [应用数学];

学科分类号：

070104 ;

摘要：

If the errors in the linear regression model are assumed to be independent with nonvanishing third and finite fourth moments, then it is possible to improve all linear estimators by so-called linear plus quadratic (LPQ) estimators. These consist of linear and quadratic terms in the endogeneous variable and depend on the unknown moments of the errors which, in general, have to be estimated from the data. In this paper, we will use LPQ estimators for quasiminimax estimation and some related problems.

引用

页码：97 / 111

页数：15

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