报 告 人：周勇 教授 中国科学院数学与系统科学研究院研究员/上海财经大学 报告题目： Some Semiparametric Model for Length-biased and Right-censored Data 时 间： 2013年 地 点： 成功楼603 主 办： 数学与计算机科学学院 参加对象： 概率论与数理统计、计算智能教研室教师和研究生 报告摘要：Length-biased sampling data are often encountered in the studies of economics, industrial reliability, etiology applications epidemiology, genetics and cancer screening. The complication of this type of data is due to the fact that the observed lifetime suffers from left truncation and right censoring, where the left truncation variable has a uniform distribution. In this talk, we intend to study the accelerated failure time model (AFT) with length-biased sampling data by using the composite partial likelihood technique (Huang and Qin, 2012). The proposed method has a very simple form. To ease the calculations for estimates, we use a kernel smoothed estimation method (Heller, 2007). Large sample results and a re-sampling method for the variance estimation are discussed. A simulation study is conducted to compare the performance of the proposed method with other existing methods. A real data set is used for illustration. Furthermore, we considers the monotonic transformation model with unspecified transformation function and unknown error function, and gives its monotone rank estimation with length-biased and right-censored data. The estimator is shown to be -consistent and asymptotically normal. Numerical simulation studies reveal good finite sample performance. The variance could be estimated by a resampling method via perturbing the U-statistics objective function repeatedly, which avoids the choice of smoothing parameters by using numerical derivatives. 专家简介： 周勇研究员主要从事统计学研究，在数量金融与风险管理、计量经济学、 生存分析和生物统计等方面做出突出贡献。曾主持与主要参加完成国家级和省部级项目7项，是国家973重大项目骨干成员(排名2)和863 重大项目主要成员。周勇研究员的研究成果曾发表在国际顶级统计杂志《Annals of Statistics》 （SCI 1区），《Journal of the American Statistical Association》（SCI 1区）和顶级计量经济学杂志《Journal of Econometrics》（SSCI 2区）等权威杂志上。论文被SCI引用212次，SCI 他引190次。
