Weighted empirical minimum distance estimators in linear errors-in-variables regression models

2021 ◽  
Author(s):  
Pei Geng ◽  
Hira L. Koul
Keyword(s):  
Regression Models ◽  
Minimum Distance ◽  
Errors In Variables ◽  
Minimum Distance Estimators

scholarly journals Fitting the Errors-in-variables Model Using High-order Cumulants and Moments

2017 ◽  
Vol 17 (1) ◽  
pp. 116-129 ◽  
Author(s):  
Timothy Erickson ◽  
Robert Parham ◽  
Toni M. Whited
Keyword(s):  
Method Of Moments ◽  
Minimum Distance ◽  
Generalized Method Of Moments ◽  
High Order ◽  
Moment Condition ◽  
Errors In Variables ◽  
Moment Estimation ◽  
Internal Support ◽  
Minimum Distance Estimators ◽  
High Order Cumulants

In this article, we consider a multiple mismeasured regressor errors-in-variables model. We present xtewreg, a command for using two-step generalized method of moments and minimum distance estimators that exploit overidentifying information contained in high-order cumulants or moments of the data. The command supports cumulant or moment estimation, internal support for the bootstrap with moment condition recentering, an arbitrary number of mismeasured regressors and perfectly measured regressors, and cumulants or moments up to an arbitrary degree. We also demonstrate how to use the estimators in the context of a corporate leverage regression.

Use of Errors-in-Variables Regression Models for Studies with K-X Ray Fluorescence Bone Lead Measurements

Epidemiology ◽  
2009 ◽  
Vol 20 ◽  
pp. S170-S171
Author(s):  
Hector Lamadrid-Figueroa ◽  
Martha M Tellez-Rojo ◽  
Gustavo Angeles ◽  
Mauricio Hernandez-Avila ◽  
Howard Hu
Keyword(s):  
Regression Models ◽  
Errors In Variables ◽  
X Ray ◽  
Bone Lead
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