Understanding WaveShrink : Variance and bias estimation BY

@inproceedings{Bruce2005UnderstandingW,
  title={Understanding WaveShrink : Variance and bias estimation BY},
  author={Andrew G. Bruce and Hong-Ye Gao},
  year={2005}
}
Donoho & Johnstone's WaveShrink procedure has proved valuable for function estimation and nonparametric regression. WaveShrink is based on the principle of shrinking wavelet coefficients towards zero to remove noise. WaveShrink has very broad asymptotic near-optimality properties and achieves the optimal risk to within a factor of log n. In this paper, we derive computationally efficient formulae for computing the exact bias, variance and L2 risk of WaveShrink estimates in finite sample… CONTINUE READING
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