Model Selection with Componentwise Shrinkage in Orthogonal Regression

Katsuyuki HAGIWARA  

Publication
IEICE TRANSACTIONS on Fundamentals of Electronics, Communications and Computer Sciences   Vol.E86-A   No.7   pp.1749-1758
Publication Date: 2003/07/01
Online ISSN: 
DOI: 
Print ISSN: 0916-8508
Type of Manuscript: PAPER
Category: Digital Signal Processing
Keyword: 
harmonic analysis,  orthogonal regression,  model selection criterion,  penalized cost function,  componentwise shrinkage estimator,  

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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.