Published by the Foundation for Open Access Statistics Editors-in-chief: Bettina Grün, Torsten Hothorn, Rebecca Killick, Edzer Pebesma, Achim Zeileis    ISSN 1548-7660; CODEN JSSOBK
[test by reto]
Authors: Donghoh Kim, Hee-Seok Oh
Title: CVTresh: R Package for Level-Dependent Cross-Validation Thresholding
Abstract: The core of the wavelet approach to nonparametric regression is thresholding of wavelet coefficients. This paper reviews a cross-validation method for the selection of the thresholding value in wavelet shrinkage of Oh, Kim, and Lee (2006), and introduces the R package CVThresh implementing details of the calculations for the procedures.

This procedure is implemented by coupling a conventional cross-validation with a fast imputation method, so that it overcomes a limitation of data length, a power of 2. It can be easily applied to the classical leave-one-out cross-validation and K-fold cross-validation. Since the procedure is computationally fast, a level-dependent cross-validation can be developed for wavelet shrinkage of data with various sparseness according to levels.

Page views:: 6691. Submitted: 2005-08-22. Published: 2006-04-08.
Paper: CVTresh: R Package for Level-Dependent Cross-Validation Thresholding     Download PDF (Downloads: 6851)
CVThresh_1.0.1.tar.gz: CVThresh_1.0.1: R source package Download (Downloads: 1403; 18KB)

DOI: 10.18637/jss.v015.i10

This work is licensed under the licenses
Paper: Creative Commons Attribution 3.0 Unported License
Code: GNU General Public License (at least one of version 2 or version 3) or a GPL-compatible license.