Korean J. Math. Vol. 22 No. 2 (2014) pp.289-305
DOI: https://doi.org/10.11568/kjm.2014.22.2.289

New selection approach for resolution and basis functions in wavelet regression

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Published: Jun 15, 2014
Keywords:
Bayes factor, Positerior model probability, Primary resolution, Wavelet basis functions, Wavelet regression
Mathematics Subject Classification:
60A05, 62C10, 62J05, 62G08

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Chun Gun Park
Kyunggi University

Abstract

In this paper we propose a new approach to the variable selection problem for a primary resolution and wavelet basis functions in wavelet regression. Most wavelet shrinkage methods focus on thresholding the wavelet coefficients, given a primary resolution which is usually determined by the sample size. However, both a primary resolution and the basis functions are affected by the shape of an unknown function rather than the sample size. Unlike existing methods, our method does not depend on the sample size and also takes into account the shape of the unknown function.


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Supporting Agencies

This research was supported by Kyonggi University Research Grant 2010

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