Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/96354
Title: Shrinkage estimation for identification of linear components in additive models
Authors: Lian, Heng
Keywords: DRNTU::Science::Mathematics
Issue Date: 2011
Source: Lian, H. (2012). Shrinkage estimation for identification of linear components in additive models. Statistics & Probability Letters, 82(2), 225-231.
Series/Report no.: Statistics & probability letters
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.
URI: https://hdl.handle.net/10356/96354
http://hdl.handle.net/10220/11922
ISSN: 0167-7152
DOI: http://dx.doi.org/10.1016/j.spl.2011.10.009
Rights: © 2011 Elsevier B.V.
Fulltext Permission: none
Fulltext Availability: No Fulltext
Appears in Collections:SPMS Journal Articles

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