articleJournal of Computational and Graphical StatisticsJan 1, 2009Closed access

Examples of Adaptive MCMC

GOGareth O. RobertsJSJeffrey S. Rosenthal

Lancaster University

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Abstract

We investigate the use of adaptive MCMC algorithms to automatically tune the Markov chain parameters during a run. Examples include the Adaptive Metropolis (AM) multivariate algorithm of Haario, Saksman, and Tamminen (2001), Metropolis-within-Gibbs algorithms for nonconjugate hierarchical models, regionally adjusted Metropolis algorithms, and logarithmic scalings. Computer simulations indicate that the algorithms perform very well compared to nonadaptive algorithms, even in high dimension.

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Topics & keywords

Topics
Keywords
  • Markov chain Monte Carlo
  • Metropolis–Hastings algorithm
  • Gibbs sampling
  • Markov chain
  • Computer science
  • Algorithm
  • Logarithm
  • Dimension (graph theory)
UN Sustainable Development Goals
  • Sustainable cities and communities
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