Convergence properties of hit–and–run samplers

DOI10.1080/15326349808807500zbMath0912.65121OpenAlexW2046366256MaRDI QIDQ4208818

Arnon Boneh, Claude Bélisle, Richard J. Caron

Publication date: 3 May 1999

Published in: Communications in Statistics. Stochastic Models (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/15326349808807500

zbMATH Keywords

convergenceMarkov chain Monte Carlo methodasymptotichit-and-run algorithmshit-and-run samplers

Mathematics Subject Classification ID

Monte Carlo methods (65C05) Applications of Markov chains and discrete-time Markov processes on general state spaces (social mobility, learning theory, industrial processes, etc.) (60J20) Probabilistic methods, stochastic differential equations (65C99)

Related Items (6)

Discovering the Characteristics of Mathematical Programs via Sampling ⋮ Exploring stochasticity and imprecise knowledge based on linear inequality constraints ⋮ Hit and Run Sampling from Tropically Convex Sets ⋮ Hit and run as a unifying device ⋮ Slow hit-and-run sampling ⋮ Slow convergence of the Gibbs sampler

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