Shrinkage estimation for identification of linear components in additive models

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

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Author(s)

Detail(s)

Original languageEnglish
Pages (from-to)225-231
Journal / PublicationStatistics and Probability Letters
Volume82
Issue number2
Publication statusPublished - Feb 2012
Externally publishedYes

Abstract

In this short paper, we demonstrate that the popular penalized estimation method typically used for variable selection in parametric or semiparametric models can actually provide a way to identify linear components in additive models. Unlike most studies in the literature, we are NOT performing variable selection. Due to the difficulty in a priori deciding which predictors should enter the partially linear additive model as the linear components, such a method will prove useful in practice. © 2011 Elsevier B.V.

Research Area(s)

  • Generalized cross-validation, Oracle property, Partially linear additive models