Consider a pair of random variables, both subject to random right censoring. New estimators for the bivariate and marginal distributions of these variables are proposed. The estimators of the marginal distributions are not the marginals of the corresponding estimator of the bivariate distribution. Both estimators require estimation of the conditional distribution when the conditioning variable is subject to censoring. Such a method of estimation is proposed. The weak convergence of the estimators proposed is obtained. A small simulation study suggests that the estimators of the marginal and bivariate distributions perform well relatively to respectively the Kaplan-Meier estimator for the marginal distribution and the estimators of Pruitt and van der Laan for the bivariate distribution. The use of the estimators in practice is illustrated by the analysis of a data set. Copyright 2003 Royal Statistical Society.
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机译：考虑一对随机变量，它们都受到随机权限检查。提出了这些变量的双变量和边际分布的新估计量。边际分布的估计量不是二元分布的相应估计量的边际量。当条件变量要经过审查时，两个估计器都需要估计条件分布。提出了这种估计方法。得到了所提出的估计量的弱收敛性。一项小型的模拟研究表明，边际和双变量分布的估计量相对于边际分布的Kaplan-Meier估计量和双变量分布的Pruitt和van der Laan估计量表现相对较好。估计器在实践中的使用通过对数据集的分析来说明。版权所有2003皇家统计学会。
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