Additive models in censored regression

被引：8

作者：

de Una Alvarez, Jacobo ^{[1
]}

Roca Pardinas, Javier ^{[1
]}

机构：

[1] Univ Vigo, Dept Estadist & IO, Fac CC Econ & Empresariales, Vigo 36310, Spain

来源：

COMPUTATIONAL STATISTICS & DATA ANALYSIS | 2009年 / 53卷 / 09期

关键词：

ASYMPTOTIC PROPERTIES; LINEAR-MODELS; COVARIABLES; INFERENCE; SELECTION;

D O I：

10.1016/j.csda.2009.02.008

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

Additive models in censored regression are considered. A randomly weighted version of the backfitting algorithm that allows for the nonparametric estimation of the effects of the covariates on the response is provided. Given the high computational cost involved, binning techniques are used to speed up the computation in the estimation and testing process. Simulation results and the application to real data reveal that the predictor obtained with the additive model performs well, and that it is a convenient alternative to the linear predictor when some nonlinear effects are expected. (C) 2009 Elsevier B.V. All rights reserved.

引用

页码：3490 / 3501

页数：12

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