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Abstract: This paper is about using wavelets for regression. The main aim of the paper is to introduce and develop a cross-validation method for selecting a wavelet regression threshold that produces good estimates with respect to L2 error. The selected threshold determines which coefficients to keep in an orthogonal wavelet expansion of noisy data and acts in a similar way to a smoothing parameter in non-parametric regression. The paper gives a very brief introduction to wavelets and how the discrete... (Update)
Context of citations to this paper: More
...shrinkage. Donoho and Johnstone propose several thresholds (i.e. universal, SURE) as well as several thresholding policies. Nason (1994) adjusted the well known crossvalidation method for use with wavelets. The threshold is selected by minimizing a cross validatory...
...between denoising threshold (and alenoising scale S0 respectively) and the alenoising performance is of interest. As described in Nason [7], an often used, universal threshold can be deter mined, only depending on the signal length and the noise standard deviation o . In...
Cited by: More
Nonlinear processing of a shift invariant DWT for noise.. - Lang Guo Odegard (Correct)
Choice of the Threshold Parameter in Wavelet Function Estimation - Nason (1995) (Correct)
Comparison and Assessment of Various Wavelet and.. - Hess, Kraft.. (Correct)
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0.5: Wavelet Shrinkage Using Cross-Validation - Nason (1996) (Correct)
0.5: Some New Statistical Approaches to the Analysis of Long Memory.. - McCoy (1994) (Correct)
0.1: The Stationary Wavelet Transform and some Statistical.. - Nason, Silverman (1995) (Correct)
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0.2: Wind Speed Modelling and Short-term Prediction using Wavelets - Hunt, Nason (Correct)
0.2: Poisson Intensity Estimation Using Wavelets and the Fisz.. - Piotr Fry'zlewicz Guy (Correct)
0.1: Fast cross-validatory choice of wavelet smoothness, primary.. - Nason (1999) (Correct)
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13: Ten Lectures on Wavelets (context) - Daubechies - 1992
13: Adapting to unknown smoothness via wavelet shrinkage - Donoho, Johnstone - 1995
13: Wavelet shrinkage: asymptopia - Donoho, Johnstone et al. - 1995
BibTeX entry: (Update)
Nason, G.P.: Wavelet regression by cross-validation. Tech. Report 447, Dep. of Stat., Stanford University (1994). http://citeseer.ist.psu.edu/nason94wavelet.html More
@techreport{ nason94wavelet,
author = "Guy P. Nason",
title = "Wavelet regression by cross-validation",
pages = "45",
year = "1994",
url = "citeseer.ist.psu.edu/nason94wavelet.html" }
Citations (may not include all citations):1064 A theory for multiresolution signal decomposition: the wavel.. (context) - Mallat - 1989
770 Orthonormal bases of compactly supported wavelets (context) - Daubechies - 1988
401 An Introduction to Wavelets (context) - Chui - 1992
227 Adapting to Unknown Smoothness via Wavelet Shrinkage - Donoho, Johnstone - 1994
202 Ideal spatial adaptation by wavelet shrinkage - Donoho, Johnstone - 1993
198 Wavelet shrinkage: asymptopia - Donoho, Johnstone et al. - 1994
60 The discrete wavelet transform in S - Nason, Silverman - 1994
45 Wavelet transforms versus Fourier transforms (context) - Strang - 1993
18 Estimation d'une densit 'e de probabilit'e par m'ethode d'on.. (context) - Johnstone, Kerkyacharian et al. - 1992
6 Adaption to high spatial inhomogeneity based on wavelets and.. (context) - Fan, Hall et al. - 1993
6 transform: an adaptive generalization of the wavelet transfo.. (context) - Mann, Haykin - 1992
3 The wavethresh package; wavelet transform and thresholding s.. (context) - Nason - 1993
2 Ten lectures on Wavelets (context) - Pure, Mathematics et al. - 1992
1 Exact reconstruction techniques for treestructured subband c.. (context) - Computational, Statistics et al. - 1986
The graph only includes citing articles where the year of publication is known.
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