Nonparametric estimation of the survival function from censored data based on relative risk function

We present a nonparametric estimator for distribution function under random censorship from the right. Our approach is based on estimating the relative risk function, and the resulting estimator is closely related with the Kaplan-Meier’s product-limit and Breslow’s exponential hazard estimators. We also consider the general proportional hazards model when the competing risks are variable censored from the left.