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Estimation and Variable Selection for Semiparametric Additive Partial Linear Models (SS-09-140)

Semiparametric additive partial linear models, containing both linear and nonlinear additive components, are more flexible compared to linear models, and they are more efficient compared to general nonparametric regression models because they reduce the problem known as “curse of dimensionality”. In...

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Detalhes bibliográficos
Main Authors: Liu, Xiang, Wang, Li, Liang, Hua
Formato: Artigo
Idioma:Inglês
Publicado em: 2011
Assuntos:
Acesso em linha:https://ncbi.nlm.nih.gov/pmc/articles/PMC3165000/
https://ncbi.nlm.nih.gov/pubmed/21894241
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.5705/ss.2009.140
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