Nonparametric density estimation from censored data

Abstract

Abstract Nonparametric estimation of the probability density function f° of a lifetime distribution based on arbitrarily right-censor-ed observations from f° has been studied extensively in recent years. In this paper the density estimators from censored data that have been obtained to date are outlined. Histogram, kernel-type, maximum likelihood, series-type, and Bayesian nonparametric estimators are included. Since estimation of the hazard rate function can be considered as giving a density estimate, all known results concerning nonparametric hazard rate estimation from censored samples are also briefly mentioned. Keywords: kernel density estimationhazard rate estimationconsistencyhistogrammaximun likelihoodnonparametric Bayes estimationlife datarandom censor-shiparbitrary right censorship