Hazard Estimation under Generalized Censoring
Statistics Theory
2013-09-04 v1 Statistics Theory
Abstract
This paper focuses on the problem of the estimation of the cumulative hazard function of a distribution on a general complete separable metric space when the data points are subject to censoring by an arbitrary adapted random set. A problem involving observability of the estimator proposed in [8] and [9] is resolved and a functional central limit theorem is proven for the revised estimator. Several examples and applications are discussed, and the validity of bootstrap methods is established in each case.
Cite
@article{arxiv.0812.2987,
title = {Hazard Estimation under Generalized Censoring},
author = {Alberto Carabarin Aguirre and B. Gail Ivanoff},
journal= {arXiv preprint arXiv:0812.2987},
year = {2013}
}
Comments
Submitted to the Electronic Journal of Statistics (http://www.i-journals.org/ejs/) by the Institute of Mathematical Statistics (http://www.imstat.org)