Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
1154112 | Statistics & Probability Letters | 2008 | 7 Pages |
Abstract
Autin [2007. Maxisets for μ-thresholding rules. Test, to appear, see ãhttp://www.seio.es/test/Archivos/issues/Ab_TESTAutin.htmlã] has established the following estimation result: by considering the Gaussian white noise model and the Besov risk Bp,p0, the BlockShrink estimator is better in the maxiset sense than the hard thresholding estimator. In the present paper, we show that this maxiset superiority is strict and can be extended to the Lp risk for numerous sophisticated models (regression with random uniform design, convolution model in Gaussian white noise,â¦).
Related Topics
Physical Sciences and Engineering
Mathematics
Statistics and Probability
Authors
Christophe Chesneau,