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The central limit theorem under random truncation

22 October 2008
W. Stute
Jane-ling Wang
ArXiv (abs)PDFHTML
Abstract

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

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