報告題目：Variable selection for generalized linear models with interval-censored failure time data
報 告 人：胡濤 教授 首都師範大學
報告時間：2022年9月21日 星期三13:30-14:30
報告地點：騰訊會議：496457998
校内聯系人：趙世舜 zhaoss@jlu.edu.cn
報告摘要：Variable selection is often needed in many fields and has been discussed by many authors in various situations. This is especially the case under linear models and when one observes complete data. Among others, one common situation where variable selection is required is to identify important risk factors from a large number of covariates. In this paper, we consider the problem when one observes interval-censored failure time data arising from generalized linear models, for which there does not seem to exist an established method. To address this, we propose a penalized least squares method with the use of an unbiased transformation and the oracle property of the method is established along with the asymptotic normality of the resulting estimators of regression parameters. Simulation studies were conducted and demonstrated that the proposed method performed well for practical situations. In addition, the method was applied to a motivating example about children’s mortality data of Nigeria.
報告人簡介：胡濤，首都師範大學數學科學學院教授，博士生導師。研究方向：生存分析、應用統計。2009年畢業于北京師範大學數學科學學院，獲概率論與數理統計專業博士學位。美國University of Missouri 統計系博士後。在國内外學術刊物Journal of the American Statistical Association、Biometrika、Renewable Energy、Energy Conversion and Management、中國科學：數學等上發表學術論文多篇。
