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http://dx.doi.org/10.11568/kjm.2014.22.2.289

NEW SELECTION APPROACH FOR RESOLUTION AND BASIS FUNCTIONS IN WAVELET REGRESSION  

Park, Chun Gun (Department of Mathematics Kyonggi University)
Publication Information
Korean Journal of Mathematics / v.22, no.2, 2014 , pp. 289-305 More about this Journal
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.
Keywords
Bayes factor; Positerior model probability; Primary resolution; Wavelet basis functions; Wavelet regression;
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