A limit theorem for testing with randomly censored data
A limit theorem for testing with randomly censored data
Here, [A] denotes indicator of event A. The X.fs are true survival times, the Y.'s are censoring times and one observes {(d.,?.), l?i?n}. This is the socalled random censoring model where often one is interested in making inferences about F or about some function of F based on {(d.,?.), l_<i_<n}. …