Is Each NPMLE of a Continuous Bivariate Distribution Function with Singly Right-Censored Data Really Inconsistent?

被引:0
|
作者
Yu, Qiqing [1 ,2 ]
Sen, Chingfu [2 ]
Huang, Jinlong [3 ]
Lee, Chinsan [2 ]
机构
[1] SUNY Binghamton, Dept Math, Binghamton, NY 13902 USA
[2] Natl Sun Yat Sen Univ, Dept Appl Math, Kaohsiung, Taiwan
[3] Kaohsiung Med Univ, Ctr Gen Educ, Kaohsiung, Taiwan
关键词
Bivariate right censoring; Bivariate survival analysis; Consistency; Generalized MLE; Nonparametric MLE; Simulation; SELF-CONSISTENT ESTIMATORS; SURVIVAL FUNCTION; NONPARAMETRIC-ESTIMATION; ASYMPTOTIC PROPERTIES; EFFICIENT ESTIMATION;
D O I
10.1080/03610920903480874
中图分类号
O21 [概率论与数理统计]; C8 [统计学];
学科分类号
020208 ; 070103 ; 0714 ;
摘要
We consider non-parametric estimation of a continuous cdf of a random vector (X1, X2). With bivariate RC data, it is stated in van der Laan (1996, p. 59810, Ann. Statist.), Quale et al. (2006, JASA) etc. that oit is well known that the NPMLE for continuous data is inconsistent (Tsai et al. (1986)).o The claim is based on a result in Tsai et al. (1986, p.1352, Ann. Statist.) that if X1 is right censored but not X2, then common ways for defining one NPMLE lead to inconsistency. If X1 is right censored and X2 is type I right-censored (which includes the case in Tsai et al.), we present a consistent NPMLE. The result corrects a common misinterpretation of Tsai's example (Tsai et al., 1986, Ann. Statist.).
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页码:844 / 862
页数:19
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