Rank Regression Methods for Left-Truncated and Right-Censored Data
Lai, Tze Leung ; Ying, Zhiliang
Ann. Statist., Tome 19 (1991) no. 1, p. 531-556 / Harvested from Project Euclid
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.
Publié le : 1991-06-14
Classification:  Censoring and truncation,  regression,  linear rank statistics,  martingales,  stochastic integrals,  empirical processes,  tightness,  asymptotic normality,  adaptive rank estimators,  62J99,  62G20,  60F05
@article{1176348110,
     author = {Lai, Tze Leung and Ying, Zhiliang},
     title = {Rank Regression Methods for Left-Truncated and Right-Censored Data},
     journal = {Ann. Statist.},
     volume = {19},
     number = {1},
     year = {1991},
     pages = { 531-556},
     language = {en},
     url = {http://dml.mathdoc.fr/item/1176348110}
}
Lai, Tze Leung; Ying, Zhiliang. Rank Regression Methods for Left-Truncated and Right-Censored Data. Ann. Statist., Tome 19 (1991) no. 1, pp.  531-556. http://gdmltest.u-ga.fr/item/1176348110/