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Central limit theorem of linear regression model under right censorship
Authors:Shuyuan?He  author-information"  >  author-information__contact u-icon-before"  >  mailto:syhe@math.pku.edu.cn"   title="  syhe@math.pku.edu.cn"   itemprop="  email"   data-track="  click"   data-track-action="  Email author"   data-track-label="  "  >Email author,Xiang?Huang
Affiliation:1. MAM and School of Mathematical Sciences, Peking University, Beijing 100871, China
2. Department of Applied Mathematics, The Hong Kong Polytechnic University, Hong Kong, China
Abstract:In this paper, the estimation of joint distribution F(y,z) of (Y, Z) and the estimation in thelinear regression model Y = b′Z + ε for complete data are extended to that of the right censored data. Theregression parameter estimates of b and the variance of ε are weighted least square estimates with randomweights. The central limit theorems of the estimators are obtained under very weak conditions and the derivedasymptotic variance has a very simple form.
Keywords:asymptotic normality   linear regression   product limit estimator   right censoring   weighted least squares.
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