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

Piero Barone, Giovanni Sebastiani and Julian Stander

Statistics & Probability Letters, 2001, vol. 52, issue 2, 115-124

Abstract: 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.

Keywords: Blocking; Image; analysis; Rate; of; convergence; Spectral; radius (search for similar items in EconPapers)
Date: 2001
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