Abstract

Abstract Wavelets have motivated development of a host of new ideas in nonparametric regression smoothing. Here we apply the too] of exact risk analysis, to understand the small sample behavior of wavelet estimators, and thus to check directly the conclusions suggested by asymptotics. Comparisons between some wavelet bases, and also between hard and soft thresholding, are given from several viewpoints. Our results provide insight as to why the viewpoints and conclusions of Donoho and Johnstone differ from those of Hall and Patil.

Keywords

WaveletViewpointsEstimatorMathematicsNonparametric regressionSmoothingRegressionStatisticsEconometricsNonparametric statisticsRegression analysisSample (material)Computer scienceArtificial intelligence

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Publication Info

Year
1998
Type
article
Volume
7
Issue
3
Pages
278-309
Citations
77
Access
Closed

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J. S. Marron, Süleyman Adak, Iain M. Johnstone et al. (1998). Exact Risk Analysis of Wavelet Regression. Journal of Computational and Graphical Statistics , 7 (3) , 278-309. https://doi.org/10.1080/10618600.1998.10474777

Identifiers

DOI
10.1080/10618600.1998.10474777