Perfect simulation for Bayesian wavelet thresholding with correlated coefficients
Methodology
2009-03-17 v1 Computation
Abstract
We introduce a new method of Bayesian wavelet shrinkage for reconstructing a signal when we observe a noisy version. Rather than making the common assumption that the wavelet coefficients of the signal are independent, we allow for the possibility that they are locally correlated in both location (time) and scale (frequency). This leads us to a prior structure which is analytically intractable, but it is possible to draw independent samples from a close approximation to the posterior distribution by an approach based on Coupling From The Past.
Cite
@article{arxiv.0903.2654,
title = {Perfect simulation for Bayesian wavelet thresholding with correlated coefficients},
author = {Graeme K. Ambler and Bernard W. Silverman},
journal= {arXiv preprint arXiv:0903.2654},
year = {2009}
}
Comments
16 pages, originally Tech Report, University of Bristol, 2004