ADAPTIVE BRIDGE REGRESSION MODELING AND SELECTION OF THE TUNING PARAMETERS - Collections

＜journal article＞
ADAPTIVE BRIDGE REGRESSION MODELING AND SELECTION OF THE TUNING PARAMETERS

Creator	Creator Name Kawano, Shuichi 川野, 秀一カワノ, シュウイチ Affiliation Affiliation Name Department of Mathematical Sciences, Graduate School of Engineering, Osaka Prefecture University 大阪府立大学大学院工学研究科数理工学分野
Language	English
Publisher	Research Association of Statistical Sciences
Publisher	統計科学研究会
Date	2012-12
Source Title	Bulletin of informatics and cybernetics
Vol	44
First Page	29
Last Page	39
Publication Type	Version of Record
Access Rights	open access
Crossref DOI	https://doi.org/10.5109/1495409
Related DOI	http://bic.math.kyushu-u.ac.jp/
Related URI	http://bic.math.kyushu-u.ac.jp/
Relation	http://bic.math.kyushu-u.ac.jp/
Abstract	We consider the problem of constructing an adaptive bridge regression modeling, which is a penalized procedure where different weights are imposed on different coefficients in a bridge penalty term. A... crucial issue in the modeling process is the choice of the adjusted parameters included in the models. Here, we treat the selection of the adjusted parameters as model selection and evaluation problems. In order to select the parameters, the model selection criteria are derived from information-theoretic and Bayesian approaches. We conduct some numerical studies to investigate the effectiveness of our proposed modeling strategy.show more

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PISSN	0286-522X
EISSN	2435-743X
NCID	AA10634475
Record ID	1495409
Peer-Reviewed	Refereed
Subject Terms	Adaptive penalty
	Bayesian approach
	Bridge regression
	Information criterion
	Penalized maximum likelihood method
Created Date	2015.03.09
Modified Date	2020.10.22