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Nonparametric estimation of lifetime distribution is a crucial issue in survival analysis. In this paper, we consider such estimation problem in a uniform martingale framework. The corresponding estimators when the observed data are subject to right censoring, random truncation, and missing-censoring are derived and the large-sample behavior of these estimators are studied by applying martingale theory.
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