English

The central limit theorem under random truncation

Statistics Theory 2008-10-23 v1 Statistics Theory

Abstract

Under left truncation, data (Xi,Yi)(X_i,Y_i) are observed only when YiXiY_i\le X_i. Usually, the distribution function FF of the XiX_i is the target of interest. In this paper, we study linear functionals φdFn\int\varphi \mathrm{d}F_n of the nonparametric maximum likelihood estimator (MLE) of FF, the Lynden-Bell estimator FnF_n. A useful representation of φdFn\int \varphi \mathrm{d}F_n is derived which yields asymptotic normality under optimal moment conditions on the score function φ\varphi. No continuity assumption on FF is required. As a by-product, we obtain the distributional convergence of the Lynden-Bell empirical process on the whole real line.

Keywords

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)

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