Variable Bandwidth Kernel Density Estimation for Censored Data
It has long been recognized that accurate estimation of the density function is an important problem for inference with censored data (see Gehan, 1969). This paper presents a new kernel type estimator, which smooths at observed lifetimes inversely proportional to their density according to Abramson’s square root law. It is shown that a similar reduction in bias is achieved.
AMS Subject Classification62G07 62N02
Key-wordsCensored data Density estimation Kaplan-Meier estimator Kernel Smoothing
Unable to display preview. Download preview PDF.
- Blum, J.R., Susarla, V., 1980. Maximal deviation theory of density and failure rate function estimates based on censored data. In Multivariate analysis, V (Proc. Fifth Internat. Sympos.), Krishnaiah, P. (Editor), Univ. Pittsburgh, 213–222.Google Scholar
- Giné, E., Sang, H., 2010. Uniform asymptotics for kernel density estimators with variable bandwidths. J. Nonpar. Stat., To appear.Google Scholar