报告题目：Nonparametric Maximum Likelihood Estimation of Semiparametric Regression Models With Censored Data

报告人：Professor Danyu Lin (UniversityofNorth CarolinaatChapel Hill)

时间：2014年6月9日（星期一）16:00:17:00

地点：理科楼数学系A304

摘要：Semiparametric regression models provide an attractive way to formulate the effects of covariates on potentially censored failure times.

The partial likelihood, which works beautifully for the Cox proportional hazards model with univariate failure time data, is not tractable for general transformation models for univariate failure time data, random-effects models for multivariate failure time data, or joint models for repeated measures and failure times. Nonparametric maximum likelihood estimation (NPMLE) provides an elegant and powerful solution to the statistical inference for such models.

The presence of infinite-dimensional parameters poses considerable theoretical and computational challenges. We show that the NPMLE is consistent, asymptotically normal and asymptotically efficient under mild conditions. We develop simple and stable numerical techniques to implement the corresponding inference procedures. Illustrations with real medical studies are provided.

报告人介绍：Danyu Lin is the Dennis Gillings Distinguished Professor of Biostatistics at theUniversityofNorth CarolinaatChapel Hill. Professor Lin is an internationally renowned statistician who has made fundamental contributions to many areas of statistics, including survival analysis and statistical genetics. He has published over 150 peer-reviewed papers, most of which appeared in top statistical journals. Several of his methods have been incorporated into commercial software packages, such as SAS, S-Plus and STATA, and widely used in practice. Professor Lin is on Thomson ISI's list of Highly Cited Researchers in Mathematics. He is a former recipient of the Mortimer Spiegelman Gold Medal from the American Public Health Association and a Fellow of both the American Statistical Association and theInstituteofMathematical Statistics. He currently serves as an Associate Editor of Biometrika and Journal of the American Statistical Association.

联系人：杨瑛