报告人：黄磊
报告地点：腾讯会议ID:226 851 474
报告时间：2022年04月12日星期二14:00-15:00
报告摘要:
Censoring often occurs in data collection. This article, considers nonparametric regression when the covariate is censored under general settings. In contrast to censoring in the response variable in survival analysis, regression with censored covariates is more challenging but less studied in the literature, especially for dependent censoring. We propose to estimate the regression function using conditional hazard rates. The asymptotic normality of our proposed estimator is established. Both theoretical results and simulation studies demonstrate that the proposed method is more efficient than the estimation based on complete observations and other methods, especially when the censoring rate is high. We illustrate the usefulness of the proposed method using a data set from the Framingham heart study and a data set from a randomized placebo-controlled clinical trial of the drug D-penicillamine.
主讲人简介:
黄磊博士2015年毕业于新加坡国立大学，现任职于西南交通大学数学学院统计系，副教授，硕士生导师，科研方向包括半参数回归模型、时间序列分析、生物和医学统计。已发表论文二十余篇, 部分论文发表在The Annals of Statistics, Journal of Business & Economic Statistics, Statistical Methods in Medical Research, Statistics in Medicine, Computational Statistics & Data Analysis, Journal of Statistical Computation and Simulation等期刊上。主持国家自科青年项目1项、四川省应用基础研究计划面上项目1项、四川省人社厅科研资助项目1项，参与国家自然科学基金面上项目和青年项目各一项。2020年获四川省数学会首届应用数学奖一等奖。
