Robust Estimation for Linear Errors-in-Variables Models With Homoscedastic Measurement Errors

Linear errors-in-variables (EIV) models with heteroscedastic measurement errors are widely adopted in applied sciences.The linear EIV model estimators, however, can be highly biased by gross errors.This paper focuses on robust estimation in linear homoscedastic EIV models.Robust estimators of the linear homoscedastic EIV models are derived from Mestimators and Lagrange multiplier method.