Estimation of Linear and Nonlinear Errors-in-Variables Models Using Validation Data
利用验证数据估计线性与非线性变量测量误差模型
Consistent estimators for linear and nonlinear regression models with measurement errors in variables in the presence of validation data are proposed. The estimation procedures are based on least squares methods with regression functions replaced by wide-sense conditional expectation functions. The methods do not depend on distributional assumptions and are robust against the misspecification of a measurement error model. They are computationally and analytically simpler…