Highly Influenced

# Wavelet Thresholding via a Bayesian

@inproceedings{Abramovich1996WaveletTV, title={Wavelet Thresholding via a Bayesian}, author={ApproachF. Abramovich and Theofanis Sapatinas and B. W. Silverman}, year={1996} }

- Published 1996

We discuss a Bayesian formalism which gives rise to a type of wavelet threshold estimation in non-parametric regression. A prior distribution is imposed on the wavelet coeecients of the unknown response function , designed to capture the sparseness of wavelet expansion common to most applications. For the prior speciied, the posterior median yields a thresholding procedure. Our prior model for the underlying function can be adjusted to give functions falling in any speciic Besov space. Weâ€¦Â CONTINUE READING

Highly Cited

This paper has 20 citations. REVIEW CITATIONS

#### From This Paper

##### Figures, tables, and topics from this paper.

15 Citations

27 References

Similar Papers

#### References

##### Publications referenced by this paper.

Showing 1-10 of 27 references

Highly Influential

Highly Influential

Highly Influential

Highly Influential

Highly Influential

Highly Influential

Highly Influential

Highly Influential

Highly Influential

Highly Influential