Model Selection with Componentwise Shrinkage in Orthogonal Regression
Summary :
In the problem of determining the major frequency components of a signal disturbed by noise, a model selection criterion has been proposed. In this paper, the criterion has been extended to cover a penalized cost function that yields a componentwise shrinkage estimator, and it exhibited a consistent model selection when the proposed criterion was used. Then, a simple numerical simulation was conducted, and it was found that the proposed criterion with an empirically estimated componentwise shrinkage estimator outperforms the original criterion.
- Publication
- IEICE TRANSACTIONS on Fundamentals Vol.E86-A No.7 pp.1749-1758
- Publication Date
- 2003/07/01
- Publicized
- Online ISSN
- DOI
- Type of Manuscript
- PAPER
- Category
- Digital Signal Processing
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Katsuyuki HAGIWARA, "Model Selection with Componentwise Shrinkage in Orthogonal Regression" in IEICE TRANSACTIONS on Fundamentals,
vol. E86-A, no. 7, pp. 1749-1758, July 2003, doi: .
Abstract: In the problem of determining the major frequency components of a signal disturbed by noise, a model selection criterion has been proposed. In this paper, the criterion has been extended to cover a penalized cost function that yields a componentwise shrinkage estimator, and it exhibited a consistent model selection when the proposed criterion was used. Then, a simple numerical simulation was conducted, and it was found that the proposed criterion with an empirically estimated componentwise shrinkage estimator outperforms the original criterion.
URL: https://global.ieice.org/en_transactions/fundamentals/10.1587/e86-a_7_1749/_p
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@ARTICLE{e86-a_7_1749,
author={Katsuyuki HAGIWARA, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={Model Selection with Componentwise Shrinkage in Orthogonal Regression},
year={2003},
volume={E86-A},
number={7},
pages={1749-1758},
abstract={In the problem of determining the major frequency components of a signal disturbed by noise, a model selection criterion has been proposed. In this paper, the criterion has been extended to cover a penalized cost function that yields a componentwise shrinkage estimator, and it exhibited a consistent model selection when the proposed criterion was used. Then, a simple numerical simulation was conducted, and it was found that the proposed criterion with an empirically estimated componentwise shrinkage estimator outperforms the original criterion.},
keywords={},
doi={},
ISSN={},
month={July},}
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TY - JOUR
TI - Model Selection with Componentwise Shrinkage in Orthogonal Regression
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 1749
EP - 1758
AU - Katsuyuki HAGIWARA
PY - 2003
DO -
JO - IEICE TRANSACTIONS on Fundamentals
SN -
VL - E86-A
IS - 7
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - July 2003
AB - In the problem of determining the major frequency components of a signal disturbed by noise, a model selection criterion has been proposed. In this paper, the criterion has been extended to cover a penalized cost function that yields a componentwise shrinkage estimator, and it exhibited a consistent model selection when the proposed criterion was used. Then, a simple numerical simulation was conducted, and it was found that the proposed criterion with an empirically estimated componentwise shrinkage estimator outperforms the original criterion.
ER -
English
