RANK REGRESSION METHODS FOR LEFT-TRUNCATED AND RIGHT-CENSORED DATA

• 成果类型: Article
• 署名作者: LAI, TL; YING, ZL
• 署名单位: University of Illinois System; University of Illinois Urbana-Champaign
• 刊物名称: ANNALS OF STATISTICS
• ISSN/ISSBN: 0090-5364
• DOI: 10.1214/aos/1176348110
• 发表日期: 1991
• 页码: 531-556
• 关键词: LINEAR-REGRESSION; tests; models

摘要

A class of rank estimators is introduced for regression analysis in the presence of both left-truncation and right-censoring on the response variable. By making use of martingale theory and a tightness lemma for stochastic integrals of multiparameter empirical processes, the asymptotic normality of the estimators is established under certain assumptions. Adaptive choice of the score functions to give asymptotically efficient rank estimators is also discussed.