Open Access
August 2008 The central limit theorem under random truncation
Winfried Stute, Jane-Ling Wang
Bernoulli 14(3): 604-622 (August 2008). DOI: 10.3150/07-BEJ116

Abstract

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

Citation

Download Citation

Winfried Stute. Jane-Ling Wang. "The central limit theorem under random truncation." Bernoulli 14 (3) 604 - 622, August 2008. https://doi.org/10.3150/07-BEJ116

Information

Published: August 2008
First available in Project Euclid: 25 August 2008

zbMATH: 1157.62017
MathSciNet: MR2537804
Digital Object Identifier: 10.3150/07-BEJ116

Keywords: central limit theorem , Lynden-Bell integral , truncated data

Rights: Copyright © 2008 Bernoulli Society for Mathematical Statistics and Probability

Vol.14 • No. 3 • August 2008
Back to Top