In this article, we study the estimation of high‐dimensional single index models when the response variable is censored. We hybrid the estimation methods for high‐dimensional single‐index models (but without censorship) and univariate nonparametric models with randomly censored responses to estimate the index parameters and the link function and apply the proposed methods to analyze a genomic dataset from a study of diffuse large B‐cell lymphoma. We evaluate the finite sample performance of the proposed procedures via simulation studies and establish large sample theories for the proposed estimators of the index parameter and the nonparametric link function under certain regularity conditions.

中文翻译：

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具有审查响应的高维单索引模型。

在本文中，我们研究了在审查响应变量时对高维单指标模型的估计。我们将高维单指标模型（但没有审查制度）的估计方法与具有随机审查响应的单变量非参数模型进行混合，以估计指标参数和链接函数，并将所提出的方法应用到来自扩散研究的分析基因组数据集大B细胞淋巴瘤 我们通过仿真研究评估了所提出程序的有限样本性能，并在一定的规律性条件下为索引参数和非参数链接函数的估计量建立了大样本理论。