Robust estimates in generalized partially linear models

Boente, Graciela; He, Xuming; Zhou, Jianhui

Boente, Graciela ; He, Xuming ; Zhou, Jianhui

Ann. Statist., Tome 34 (2006) no. 1, p. 2856-2878 / Harvested from Project Euclid

Résumé

In this paper, we introduce a family of robust estimates for the parametric and nonparametric components under a generalized partially linear model, where the data are modeled by y_i|(x_i, t_i)∼F(⋅, μ_i) with μ_i=H(η(t_i)+x_i^Tβ), for some known distribution function F and link function H. It is shown that the estimates of β are root-n consistent and asymptotically normal. Through a Monte Carlo study, the performance of these estimators is compared with that of the classical ones.

Publié le : 2006-12-15
Classification: Kernel weights, partially linear models, rate of convergence, robust estimation, smoothing, 62F35, 62G08

@article{1179935067,
     author = {Boente, Graciela and He, Xuming and Zhou, Jianhui},
     title = {Robust estimates in generalized partially linear models},
     journal = {Ann. Statist.},
     volume = {34},
     number = {1},
     year = {2006},
     pages = { 2856-2878},
     language = {en},
     url = {http://dml.mathdoc.fr/item/1179935067}
}

Boente, Graciela; He, Xuming; Zhou, Jianhui. Robust estimates in generalized partially linear models. Ann. Statist., Tome 34 (2006) no. 1, pp.  2856-2878. http://gdmltest.u-ga.fr/item/1179935067/