Asymptotic properties of an estimator in errors-in-variables models in the presence of validation data

被引：0

作者：

Fazekas, I

Baran, S

Lauridsen, J

机构：

[1] Debrecen Univ Med, Inst Math & Informat, H-4010 Debrecen, Hungary

[2] Odense Univ, Dept Stat & Demog, DK-5230 Odense M, Denmark

来源：

COMPUTERS & MATHEMATICS WITH APPLICATIONS | 1999年 / 38卷 / 5-6期

关键词：

measurement errors; errors-in-variables; validation; mixing property; consistency of estimators; random fields;

D O I：

10.1016/S0898-1221(99)00212-6

中图分类号：

O29 [应用数学];

学科分类号：

070104 ;

摘要：

Structural errors-in-variables models with dependent spatial observations are studied. The presence of validation data is assumed. An estimator for regression parameters proposed by Lee and Sepanski [1] is studied. Consistency and asymptotic normality of the estimator are established in the case of increasing domain. Infill asymptotic properties are described. Simulation results are also presented. (C) 1999 Elsevier Science Ltd. All rights reserved.

引用

页码：31 / 39

页数：9

共 9 条

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