Wavelet Based Estimate for Non-Linear and Non-Stationary Auto-Regressive Model - Collections

＜preprint＞
Wavelet Based Estimate for Non-Linear and Non-Stationary Auto-Regressive Model

Creator	Author PID L003330 Creator Name Fujii, Toru 藤井, 亨フジイ, トオル Affiliation Affiliation Name Graduate School of Mathematics, Kyushu University 九州大学大学院数理学研究院
Creator	Author PID K000492 Creator Name Yanagawa, Takashi 柳川, 堯ヤナガワ, タカシ Affiliation Affiliation Name Graduate School of Mathematics, Kyushu University 九州大学大学院数理学研究院
Language	English
Publisher	Faculty of Mathematics, Kyushu University
Publisher	九州大学大学院数理学研究院
Date	2003-12-31
Source Title	MHF Preprint Series
Vol	MHF2003-9
Publication Type	Author's Original
Access Rights	open access
Related DOI	MHF Preprint Series \|\| 2003-9 \|\| p1-34
Related DOI	http://www.math.kyushu-u.ac.jp/gakufu/
Related URI	MHF Preprint Series \|\| 2003-9 \|\| p1-34
Related URI	http://www.math.kyushu-u.ac.jp/gakufu/
Relation	MHF Preprint Series \|\| 2003-9 \|\| p1-34
Relation	http://www.math.kyushu-u.ac.jp/gakufu/
Abstract	The wavelet estimator of regression function in a non-linear auto-regressive model for non-stationary time series data is proposed. A convergence theorem of the estimators, and also related theorems, ...is developed. Cross-Validation criterion is proposed for the optimum selection of parameters. The criterion is justified by the $ alpha $-mixing condition. Finally, the method is applied to the electroencephalograph (EEG) data.show more

File	FileType	Size	Views	Description
2003-9	pdf	358 KB	181

Record ID	3342
Peer-Reviewed	Unrefereed
Subject Terms	Alpha-mixing
	Cross-validation
	Linear wavelet estimator
	Smoothing function
	Speed of convergence
	Time series
Notes	Kyushu University 21st Century COE Program Development of Dynamic Mathematics with High Functionality
Notes	九州大学21世紀COEプログラム「機能数理学の構築と展開」
Type	プレプリント
Created Date	2009.04.22
Modified Date	2018.02.21