Errors in variables regression;
Measurement error;
Linear structural model;
Method of moments;
Variance-covariance matrix;
MEASUREMENT ERROR;
REGRESSION MODEL;
VARIABLES;
SUBJECT;
D O I:
10.1016/j.stamet.2010.12.002
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:
In recent years there has been renewed interest in errors in variables regression models, where there are errors in the predictor variables as well as the dependent variable. Despite recent advances, the theory of the simple linear errors in variables model does not yet match the well known methodology of simple linear regression. This paper fills one of these gaps by presenting results for the straight line errors in variables model that will enable a practitioner to estimate not only the parameters of the model but also the approximate variances of these estimates. Attention is therefore focused on the variances of the model and the extraction of estimates. The presentation adopts a method of moments approach, but connections are made with the method of least squares and the maximum likelihood approach. (C) 2011 Elsevier B.V. All rights reserved.
机构:
Univ Appl Sci Velika Gorica, Zagrebacka Cesta 5, Velika Gorica 10410, CroatiaUniv Appl Sci Velika Gorica, Zagrebacka Cesta 5, Velika Gorica 10410, Croatia
Golubic, Iva
Marovt, Janko
论文数: 0引用数: 0
h-index: 0
机构:
Univ Maribor, Fac Econ & Business, Razlagova 14, SI-2000 Maribor, SloveniaUniv Appl Sci Velika Gorica, Zagrebacka Cesta 5, Velika Gorica 10410, Croatia
机构:
Univ Appl Sci Velika Gorica, Zagrebacka Cesta 5, Velika Gorica 10410, CroatiaUniv Appl Sci Velika Gorica, Zagrebacka Cesta 5, Velika Gorica 10410, Croatia
Golubic, Iva
Marovt, Janko
论文数: 0引用数: 0
h-index: 0
机构:
Univ Maribor, Fac Econ & Business, Razlagova 14, SI-2000 Maribor, Slovenia
IMFM, Jadranska 19, SI-1000 Ljubljana, SloveniaUniv Appl Sci Velika Gorica, Zagrebacka Cesta 5, Velika Gorica 10410, Croatia