A new strategy for speeding Markov chain Monte Carlo algorithms
โ Scribed by Antonietta Mira; Daniel J. Sargent
- Book ID
- 110544366
- Publisher
- Springer
- Year
- 2003
- Tongue
- English
- Weight
- 689 KB
- Volume
- 12
- Category
- Article
- ISSN
- 1613-981X
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๐ SIMILAR VOLUMES
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.
## Abstract Effective relaxation processes for difficult systems like proteins or spin glasses require special simulation techniques that permit barrier crossing to ensure ergodic sampling. Numerous adaptations of the venerable Metropolis Monte Carlo (MMC) algorithm have been proposed to improve it