Simulating posterior Gibbs distributions: a comparison of the Swendsen-Wang and Gibbs sampler methods |
| |
Authors: | A. J. Gray |
| |
Affiliation: | (1) Department of Statistics and Modelling Science, University of Strathclyde, G1 1XH Glasgow, UK |
| |
Abstract: | We show in detail how the Swendsen-Wang algorithm, for simulating Potts models, may be used to simulate certain types of posterior Gibbs distribution, as a special case of Edwards and Sokal (1988), and we empirically compare the behaviour of the algorithm with that of the Gibbs sampler. Some marginal posterior mode and simulated annealing image restorations are also examined. Our results demonstrate the importance of the starting configuration. If this is inappropriate, the Swendsen-Wang method can suffer from critical slowing in moderately noise-free situations where the Gibbs sampler convergence is very fast, whereas the reverse is true when noise level is high. |
| |
Keywords: | Markov random fields posterior Gibbs distributions simulation Swendsen-Wang algorithm Gibbs sampler restoration monitoring convergence |
本文献已被 SpringerLink 等数据库收录! |
|