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Giné, E. and Guillou, A. (2001) On Consistency of Kernel Density Estimators for Randomly Censored Data. Annales de l’Institut Henri Poincare (B) Probability and Statistics, 37, 503-522.

has been cited by the following article:

• TITLE: Nelson-Aalen and Kaplan-Meier Estimators in Competing Risks

  AUTHORS: Didier Alain Njamen-Njomen, Joseph Ngatchou-Wandji

  KEYWORDS: Censored Data; Counting Process; Competitive Risk; Non-Parametric Estimators; The Cumulative Incidence Function; Risk Function Specific Cause; Conditional Distribution Function

  JOURNAL NAME: Applied Mathematics, Vol.5 No.4, March 18, 2014

  ABSTRACT: In this paper, stochastic processes developed by Aalen [1][2] are adapted to the Nelson-Aalen and Kaplan-Meier[3] estimators in a context of competing risks. We focus only on the probability distributions of complete downtime individuals whose causes are known and which bring us to consider a partition of individuals into sub-groups for each cause. We then study the asymptotic properties of nonparametric estimators obtained.