Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Perfect simulation for Bayesian wavelet thresholding with correlated
  coefficients   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.

29
The categories of this paper are: funct-an
20
The categories of this paper are: acc-phys
18
The categories of this paper are: econ
6
The categories of this paper are: astro-ph
37
The categories of this paper are: supr-con
21
The categories of this paper are: adap-org
9
The categories of this paper are: nlin
19
The categories of this paper are: eess
27
The categories of this paper are: comp-gas
1
The categories of this paper are: cs
26
The categories of this paper are: bayes-an
28
The categories of this paper are: alg-geom
33
The categories of this paper are: plasm-ph
0
The categories of this paper are: hep-ph
30
The categories of this paper are: q-alg
8
The categories of this paper are: hep-ex