Nonparametric Censored and Truncated Regression
提出非参数删失与截断回归模型中潜在回归函数的新估计量，仅需两次非参数回归和一元积分，并证明基于局部线性核估计的一致性及渐近正态性，还允许异方差存在。
This paper proposes new estimators of the latent regression function in nonparametric censored and truncated regression models. Our estimators are computationally convenient, consisting only of two nonparametric regressions and a univariate integral. We establish consistency and asymptotic normality for an implementation based on local linear kernel estimators. An extension permits estimation in the presence of a general form of heteroscedasticity.