Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/12806
Title: Central limit theorem of linear regression model under right censorship
Authors: He, SY
Huang, X. 
Keywords: Asymptotic normality
Linear regression
Product limit estimator
Right censoring
Weighted least squares
Issue Date: 2003
Publisher: Science China Press
Source: Science in China series a - mathematics, 2003, v. 46, no. 5, p. 600-610 How to cite?
Journal: Science in China Series A-Mathematics 
Abstract: In this paper, the estimation of joint distribution F(y, z) of (Y, Z) and the estimation in the linear regression model Y = b'Z + epsilon for complete data are extended to that of the right censored data. The regression parameter estimates of b and the variance of e are weighted least square estimates with random weights. The central limit theorems of the estimators are obtained under very weak conditions and the derived asymptotic variance has a very simple form.
URI: http://hdl.handle.net/10397/12806
ISSN: 1006-9283
DOI: 10.1360/02ys0139
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