Errors-in-variables regression using estimated latent variables
提出一种利用未观测解释变量的自然估计来估计含测量误差数据回归参数的方法，证明该估计量在线性回归、probit模型及删截或截断回归模型中一致，但在非线性回归中一般不一致。
This note considers a method for estimating regression parameters from the data containing measurement errors using some natural estimates of the unobserved explanatory variables. It is shown that the resulting estimator is consistent not only in the usual linear regression model but also in the probit model and regression models with censoship or truncation. However, it fails to be consistent in nonlinear regression models except for special cases.