Robust estimates in generalized partially linear models

• 成果类型: Article
• 署名作者: Boente, Graciela; He, Xuming; Zhou, Jianhui
• 署名单位: University of Buenos Aires; University of Buenos Aires; University of Illinois System; University of Illinois Urbana-Champaign; University of Virginia; Consejo Nacional de Investigaciones Cientificas y Tecnicas (CONICET)
• 刊物名称: ANNALS OF STATISTICS
• ISSN/ISSBN: 0090-5364
• DOI: 10.1214/009053606000000858
• 发表日期: 2006
• 页码: 2856-2878
• 关键词: regression-models; Nonparametric Regression; logistic-regression; smoothing splines; likelihood

摘要

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)vertical bar(x(i), t(i)) similar to F (center dot, mu(i)) with mu(i) = H(eta(t(i)) +X-i(t) beta), for some known distribution function F and link function H. It is shown that the estimates of fi 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.