arXiv · 0708.0165
Robust estimates in generalized partially linear models
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 $y_i|(\mathbf{x}_i,t_i)\sim F(\cdot,μ_i)$ with $μ_i=H(η(t_i)+\mathbf{x}_i^{$\mathrm{T}$}β)$, 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.
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Graciela Boente, Xuming He, Jianhui Zhou. 2007-08-01. Robust estimates in generalized partially linear models. https://doi.org/10.1214/009053606000000858
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