The central limit theorem under random truncation
Statistics Theory
2008-10-23 v1 Statistics Theory
Abstract
Under left truncation, data are observed only when . Usually, the distribution function of the is the target of interest. In this paper, we study linear functionals of the nonparametric maximum likelihood estimator (MLE) of , the Lynden-Bell estimator . A useful representation of is derived which yields asymptotic normality under optimal moment conditions on the score function . No continuity assumption on is required. As a by-product, we obtain the distributional convergence of the Lynden-Bell empirical process on the whole real line.
Cite
@article{arxiv.0810.3985,
title = {The central limit theorem under random truncation},
author = {Winfried Stute and Jane-Ling Wang},
journal= {arXiv preprint arXiv:0810.3985},
year = {2008}
}
Comments
Published in at http://dx.doi.org/10.3150/07-BEJ116 the Bernoulli (http://isi.cbs.nl/bernoulli/) by the International Statistical Institute/Bernoulli Society (http://isi.cbs.nl/BS/bshome.htm)