标题： 单指标回归模型与右删失响应 显示英文标题

标题： Single-index Regression models with right-censored responses

摘要： 本文中，我们提出了一些新的M估计方法的广义化，用于处理存在随机右删失响应的单指标回归模型。 我们推导了这些估计量的一致性和渐近正态性。 结果证明是为了适应删失回归框架下广泛使用的方法（例如合成数据或加权最小二乘法）。 与非删失情况一样，单指标参数的估计器显示出与完全参数化方案相同的渐近行为。 我们通过模拟研究将这些新估计器与基于Burke和Lu（2005年）平均导数技术的估计器进行了比较。 显示英文摘要

摘要： In this article, we propose some new generalizations of M-estimation procedures for single-index regression models in presence of randomly right-censored responses. We derive consistency and asymptotic normality of our estimates. The results are proved in order to be adapted to a wide range of techniques used in a censored regression framework (e.g. synthetic data or weighted least squares). As in the uncensored case, the estimator of the single-index parameter is seen to have the same asymptotic behavior as in a fully parametric scheme. We compare these new estimators with those based on the average derivative technique of Burke and Lu (2005) through a simulation study.