Block updating in constrained Markov chain Monte Carlo sampling

Merrilee A. Hum, Håvard Rue and Nuala A. Sheehan

Statistics & Probability Letters, 1999, vol. 41, issue 4, 353-361

Abstract: 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.

Keywords: Constrained; distributions; Importance; sampling; Irreducibility; Markov; chain; Monte; Carlo; Multiple-site; updating; Stochastic; simulation; optimisation (search for similar items in EconPapers)
Date: 1999
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Citations: View citations in EconPapers (1)

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