This paper provides an empirical Bayes approach to the problem of nonparametric estimation of a distribution (or survival) function when the observations are censored on the right. The results use the notion of a Dirichlet process prior introduced by Ferguson. The paper presents a generalization to the case of right censored observations of the rate result of an empirical Bayes nonparametric estimator of a distribution function of Korwar and Hollander in the uncensored case. The rate of asymptotic convergence of optimality is shown to be the best obtainable for the problem considered.
"Empirical Bayes Estimation of a Distribution (Survival) Function from Right Censored Observations." Ann. Statist. 6 (4) 740 - 754, July, 1978. https://doi.org/10.1214/aos/1176344249