Shrinkage estimation for identification of linear components in additive models

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 vari...

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Main Author: Lian, Heng
Other Authors: School of Physical and Mathematical Sciences
Format: Article
Language:English
Published: 2013
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Online Access:https://hdl.handle.net/10356/96354
http://hdl.handle.net/10220/11922
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-963542020-03-07T12:34:41Z Shrinkage estimation for identification of linear components in additive models Lian, Heng School of Physical and Mathematical Sciences DRNTU::Science::Mathematics 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. 2013-07-22T02:50:37Z 2019-12-06T19:29:26Z 2013-07-22T02:50:37Z 2019-12-06T19:29:26Z 2011 2011 Journal Article Lian, H. (2012). Shrinkage estimation for identification of linear components in additive models. Statistics & Probability Letters, 82(2), 225-231. 0167-7152 https://hdl.handle.net/10356/96354 http://hdl.handle.net/10220/11922 10.1016/j.spl.2011.10.009 en Statistics & probability letters © 2011 Elsevier B.V.
institution Nanyang Technological University
building NTU Library
country Singapore
collection DR-NTU
language English
topic DRNTU::Science::Mathematics
spellingShingle DRNTU::Science::Mathematics
Lian, Heng
Shrinkage estimation for identification of linear components in additive models
description 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.
author2 School of Physical and Mathematical Sciences
author_facet School of Physical and Mathematical Sciences
Lian, Heng
format Article
author Lian, Heng
author_sort Lian, Heng
title Shrinkage estimation for identification of linear components in additive models
title_short Shrinkage estimation for identification of linear components in additive models
title_full Shrinkage estimation for identification of linear components in additive models
title_fullStr Shrinkage estimation for identification of linear components in additive models
title_full_unstemmed Shrinkage estimation for identification of linear components in additive models
title_sort shrinkage estimation for identification of linear components in additive models
publishDate 2013
url https://hdl.handle.net/10356/96354
http://hdl.handle.net/10220/11922
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