The Annals of Statistics

Rank Regression Methods for Left-Truncated and Right-Censored Data

Tze Leung Lai and Zhiliang Ying

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Abstract

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.

Article information

Source
Ann. Statist., Volume 19, Number 2 (1991), 531-556.

Dates
First available in Project Euclid: 12 April 2007

Permanent link to this document
https://projecteuclid.org/euclid.aos/1176348110

Digital Object Identifier
doi:10.1214/aos/1176348110

Mathematical Reviews number (MathSciNet)
MR1105835

Zentralblatt MATH identifier
0739.62031

JSTOR
links.jstor.org

Subjects
Primary: 62J99: None of the above, but in this section
Secondary: 62G20: Asymptotic properties 60F05: Central limit and other weak theorems

Keywords
Censoring and truncation regression linear rank statistics martingales stochastic integrals empirical processes tightness asymptotic normality adaptive rank estimators

Citation

Lai, Tze Leung; Ying, Zhiliang. Rank Regression Methods for Left-Truncated and Right-Censored Data. Ann. Statist. 19 (1991), no. 2, 531--556. doi:10.1214/aos/1176348110. https://projecteuclid.org/euclid.aos/1176348110


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