General over-relaxation Markov chain Monte Carlo algorithms for Gaussian densities

✍ Scribed by Piero Barone; Giovanni Sebastiani; Julian Stander

• Publisher: Elsevier Science
• Year: 2001
• Tongue: English
• Weight: 128 KB
• Volume: 52
• Category: Article
• ISSN: 0167-7152
• DOI: 10.1016/s0167-7152(00)00165-6

✦ Synopsis

We study general over-relaxation Markov chain Monte Carlo samplers for multivariate Gaussian densities. We provide conditions for convergence based on the spectral radius of the transition matrix and on detailed balance. We illustrate these algorithms using an image analysis example.