a b s t r a c tLet (T i ) 1≤i≤n be a sample of independent and identically distributed (iid) random variables (rv) of interest and (X i ) 1≤i≤n be a corresponding sample of covariates. In censorship models the rv T is subject to random censoring by another rv C . Let θ (x) be the conditional mode function of the density of T given X = x. In this work we define a new smooth kernel estimatorθ n (x) of θ (x) and establish its almost sure convergence and asymptotic normality.An application to prediction and confidence bands is also given. Simulations are drawn to lend further support to our theoretical results for finite sample sizes.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.