This article studies the large sample behavior of the censored data least squares estimator derived from the synthetic data method proposed by Leurgans and Zheng. The asymptotic distributions are derived by representing the estimator as a martingale plus a higher-order remainder term. Recently developed counting process techniques are used. The results are then compared to the censored regression estimator of Koul, Susarla and Van Ryzin.
Publié le : 1992-06-14
Classification:
Censored data,
linear regression,
asymptotic distribution,
62G10,
62P10,
62N05
@article{1176348667,
author = {Zhou, Mai},
title = {Asymptotic Normality of the `Synthetic Data' Regression Estimator for Censored Survival Data},
journal = {Ann. Statist.},
volume = {20},
number = {1},
year = {1992},
pages = { 1002-1021},
language = {en},
url = {http://dml.mathdoc.fr/item/1176348667}
}
Zhou, Mai. Asymptotic Normality of the `Synthetic Data' Regression Estimator for Censored Survival Data. Ann. Statist., Tome 20 (1992) no. 1, pp. 1002-1021. http://gdmltest.u-ga.fr/item/1176348667/