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                                       Details for article 26 of 54 found articles
 
 
  Multiple-site updates in maximum a posteriori and marginal posterior modes image estimation
 
 
Title: Multiple-site updates in maximum a posteriori and marginal posterior modes image estimation
Author: Hurn, Merrilee
Jennison, Christopher
Appeared in: Journal of applied statistics
Paging: Volume 20 (1993) nr. 5-6 pages 155-186
Year: 1993
Contents: We describe standard single-site Monte Carlo Markov chain methods, the Hastings and Metropolis algorithms, the Gibbs sampler and simulated annealing, for maximum a posteriori and marginal posterior modes image estimation. These methods can experience great difficulty in traversing the whole image space in a finite time when the target distribution is multi-modal. We present a survey of multiple-site update methods, including Swendsen and Wang's algorithm, coupled Markov chains and cascade algorithms designed to tackle the problem of moving between modes of the posterior image distribution. We compare the performance of some of these algorithms for sampling from degraded and non-degraded Ising models
Publisher: Taylor & Francis
Source file: Elektronische Wetenschappelijke Tijdschriften
 
 

                             Details for article 26 of 54 found articles
 
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