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General over-relaxation Markov chain Monte Carlo algorithms for Gaussian densities. (English) Zbl 0987.60087
The authors consider sampling $$n$$-dimensional random vectors from a Gaussian density with a positive definite covariance matrix. They examine various blocking and over-relaxation strategies which lead to a considerable reduction in the number of iterations required for convergence. These algorithms are illustrated using an image analysis problem.

##### MSC:
 60J22 Computational methods in Markov chains
##### Keywords:
blocking; image analysis; rate of convergence; spectral radius
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##### References:
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