A Cramer-Rao type inequality for estimating a hazard with censoring

Abstract : Two very active areas of statistical research are non-parametric function estimation and analysis of censored survival data. A minimax asymptotic rate of convergence for the estimation of a hazard is obtained, in the presence of random right censoring using the link between the Kullback–Leibler distance of two probabilities and a weighted Lp-type distance between their corresponding hazards.