An ergodicity result for adaptive Langevin algorithms

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Marshall, Tristan; Roberts, Gareth O.;
(2009)
  • Publisher: University of Warwick. Centre for Research in Statistical Methodology
  • Subject: QA

We consider a class of adaptive MCMC algorithms using a Langevin-type\ud proposal density. We prove that these are algorithms are ergodic\ud when the target density has exponential tail behaviour. Unlike previous\ud results, our approach does not require bounding the dr... View more
  • References (2)

    [2] Peter J. Diggle Anders Brix. Spatiotemporal prediction for log-gaussian cox processes. Journal of the Royal Statistical Society: Series B (Statistical Methodology), 63(4):823-841, 2001.

    [23] G.O. Roberts and R.L. Tweedie. Geometric convergence and central limit theorems for multidimensional hastings and metropolis algorithms. Biometrika, 83(1):95-110, 1996.

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