Shrinkage estimation for identification of linear components in additive models
Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review
Author(s)
Detail(s)
Original language | English |
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Pages (from-to) | 225-231 |
Journal / Publication | Statistics and Probability Letters |
Volume | 82 |
Issue number | 2 |
Publication status | Published - Feb 2012 |
Externally published | Yes |
Link(s)
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
Citation Format(s)
Shrinkage estimation for identification of linear components in additive models. / Lian, Heng.
In: Statistics and Probability Letters, Vol. 82, No. 2, 02.2012, p. 225-231.
In: Statistics and Probability Letters, Vol. 82, No. 2, 02.2012, p. 225-231.
Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review