TY - JOUR
T1 - Robust estimates in generalized partially linear models
AU - Boente, Graciela
AU - He, Xuming
AU - Zhou, Jianhui
PY - 2006/12
Y1 - 2006/12
N2 - 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), with 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.
AB - 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), with 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.
KW - Kernel weights
KW - Partially linear models
KW - Rate of convergence
KW - Robust estimation
KW - Smoothing
UR - http://www.scopus.com/inward/record.url?scp=34547309721&partnerID=8YFLogxK
U2 - 10.1214/009053606000000858
DO - 10.1214/009053606000000858
M3 - Article
AN - SCOPUS:34547309721
SN - 0090-5364
VL - 34
SP - 2856
EP - 2878
JO - Annals of Statistics
JF - Annals of Statistics
IS - 6
ER -