Robust estimates in generalized partially linear models

Graciela Boente, Xuming He, Jianhui Zhou

The Annals of Statistics · 2006 · Volume 34 · Issue 6

Abstract

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 yi|(xi, ti)∼F(⋅, μi) with μi=H(η(ti)+xiTβ), 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.

Keywords

62F35, 62G08, Kernel weights, partially linear models, rate of convergence, robust estimation, smoothing

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