We prove functional limit laws for the increment functions of
empirical processes based upon randomly right-censored data. The increment
sizes we consider are classified into different classes covering the whole
possible spectrum. We apply these results to obtain a description of the strong
limiting behavior of a series of estimators of local functionals of lifetime
distributions. In particular, we treat the case of kernel density and hazard
rate estimators.
Publié le : 2000-06-14
Classification:
Density and hazard rate estimation,
functional law of the iterated logarithm,
random censorship,
strong limit theorems,
62G05,
60F15,
60F17,
62E20,
62P10
@article{1019160336,
author = {Deheuvels, Paul and Einmahl, John H. J.},
title = {Functional limit laws for the increments of Kaplan-Meier
product-limit processes and applications},
journal = {Ann. Probab.},
volume = {28},
number = {1},
year = {2000},
pages = { 1301-1335},
language = {en},
url = {http://dml.mathdoc.fr/item/1019160336}
}
Deheuvels, Paul; Einmahl, John H. J. Functional limit laws for the increments of Kaplan-Meier
product-limit processes and applications. Ann. Probab., Tome 28 (2000) no. 1, pp. 1301-1335. http://gdmltest.u-ga.fr/item/1019160336/