Maximum Likelihood Estimator for the Proportional Hazards Model with Incomplete Information  

作　　者：CHEN Yurong LIU Luqin 

机构地区：[1]School of Mathematics and Statistics,Wuhan University,Wuhan 430072,Hubei,China

出　　处：《Wuhan University Journal of Natural Sciences》2012年第2期97-102,共6页武汉大学学报（自然科学英文版）

基　　金：Supported by the National Natural Science Foundation of China (10771163)

摘　　要：Right randomly censored data with incomplete infor-mation are frequently met in practice.Although much study about right randomly censored data has been seen in the proportional hazards model,relatively little is known about the inference of regression parameters for right randomly censored data with in-complete information in such model.In particular,theoretical properties of the maximum likelihood estimator of the regression parameters have not been proven yet in that model.In this paper,we show the consistency and asymptotic normality of the maxi-mum likelihood estimator of unknown regression parameters.Right randomly censored data with incomplete infor-mation are frequently met in practice.Although much study about right randomly censored data has been seen in the proportional hazards model,relatively little is known about the inference of regression parameters for right randomly censored data with in-complete information in such model.In particular,theoretical properties of the maximum likelihood estimator of the regression parameters have not been proven yet in that model.In this paper,we show the consistency and asymptotic normality of the maxi-mum likelihood estimator of unknown regression parameters.

关 键 词：proportional hazards model incomplete information maximum likelihood estimator 

分 类 号：O213[理学—概率论与数理统计]