NONPARAMETRIC BIVARIATE ESTIMATION WITH RANDOMLY CENSORED-DATA
成果类型：
Article
署名作者：
CAMPBELL, G
署名单位：
Purdue University System; Purdue University
刊物名称：
BIOMETRIKA
ISSN/ISSBN：
0006-3444
DOI：
10.2307/2335587
发表日期：
1981
页码：
417422
关键词：
摘要：
The estimation of a bivariate distribution function with randomly censored data is considered. [Times to death or times to initial contraction of a disease are of interest for litter mate pairs of rats or for twin studies in humans. The time to a deterioration level or the time to reaction of a treatment is of interest in pairs of lungs, kidneys, eyes or ears of humans.] It is assumed that the censoring occurs independently of the lifetimes and that deaths and losses which occur simultaneously can be separated. Two estimators are developed: a reduced-sample estimator and a self-consistent one. It is shown that the latter estimator satisfies a nonparametric likelihood function and is unique up to the final uncensored values in any dimension; it jumps at the points of double deaths in both dimensions.