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Change-point approach to data analytic wavelet thresholding
Authors:Todd Ogden  Emanuel Parzen
Institution:(1) Department of Statistics, University of South Carolina, 29208 Columbia, SC, USA;(2) Department of Statistics, Texas A&M University, 77843-3143 College Station, TX, USA
Abstract:Previous proposals in data dependent wavelet threshold selection have used only the magnitudes of the wavelet coefficients in choosing a threshold for each level. Since a jump (or other unusual feature) in the underlying function results in several non-zero coefficients which are adjacent to each other, it is possible to use change-point approaches to take advantage of the information contained in the relative position of the coefficients as well as their magnitudes. The method introduced here represents an initial step in wavelet thresholding when coefficients are kept in the original order.
Keywords:nonparametric regression  jump detection  Brownian bridge  Kolmogorov-Smirnov
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