SELECTION OF ARX MODELS ESTIMATED BY THE PENALIZED WEIGHTED LEAST SQUARES METHOD - Collections

＜journal article＞
SELECTION OF ARX MODELS ESTIMATED BY THE PENALIZED WEIGHTED LEAST SQUARES METHOD

Creator	Author PID K004143 Creator Name Qin, Pan 秦, 攀 Affiliation Affiliation Name Faculty of Mathematics, Kyushu University 九州大学数理学研究院
Creator	Author PID K002495 Creator Name Nishii, Ryuei 西井, 龍映 Affiliation Affiliation Name Faculty of Mathematics, Kyushu University 九州大学数理学研究院
Language	English
Publisher	Research Association of Statistical Sciences
Publisher	統計科学研究会
Date	2010-12
Source Title	Bulletin of informatics and cybernetics
Vol	42
First Page	35
Last Page	43
Publication Type	Version of Record
Access Rights	open access
Crossref DOI	https://doi.org/10.5109/25904
Related DOI	Bulletin of informatics and cybernetics \|\| 42 \|\| p35-43
Related DOI	http://bic.math.kyushu-u.ac.jp/
Related URI	Bulletin of informatics and cybernetics \|\| 42 \|\| p35-43
Related URI	http://bic.math.kyushu-u.ac.jp/
Relation	Bulletin of informatics and cybernetics \|\| 42 \|\| p35-43
Relation	http://bic.math.kyushu-u.ac.jp/
Abstract	We consider the selection problem of auto-regressive time-series models with eXogeneous variables (ARX) estimated by Penalized Weighted Least Squares (PWLS) method. AIC and BIC are developed based on ...the maximum likelihood estimation. Therefore, in this research, we evaluate GIC for the ARX models estimated by PWLS. In a numerical experiment, the model selected by GIC shows an excellent performance, especially, in a target region.show more

File	FileType	Size	Views	Description
p035	pdf	420 KB	436

PISSN	0286-522X
NCID	AA10634475
Record ID	25904
Peer-Reviewed	Refereed
Subject Terms	AIC
	auto-regressive time-series models with exogeneous variables
	BIC
	GIC
	MLE
	Model selection
	System identification.
Type	学術雑誌論文
Created Date	2013.02.07
Modified Date	2020.10.26