Block updating in constrained Markov chain Monte Carlo sampling

Markov chain Monte Carlo methods are widely used to study highly structured stochastic systems. However, when the system is subject to constraints, it is difficult to find irreducible proposal distributions. We suggest a "block-wise" approach for constrained sampling and optimisation.

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Year of publication:	1999
Authors:	Hum, Merrilee A. ; Rue, Håvard ; Sheehan, Nuala A.
Published in:	Statistics & Probability Letters. - Elsevier, ISSN 0167-7152. - Vol. 41.1999, 4, p. 353-361
Publisher:	Elsevier
Keywords:	Constrained distributions Importance sampling Irreducibility Markov chain Monte Carlo Multiple-site updating Stochastic simulation optimisation

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Type of publication:	Article
Source:	RePEc - Research Papers in Economics

Persistent link: https://www.econbiz.de/10005223025