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1 results

  • The Containment Condition and Adapfail Algorithms

  • Part of
  • Krzysztof Łatuszyński, Jeffrey S. Rosenthal
  • Journal:
    Journal of Applied Probability / Volume 51 / Issue 4 / December 2014
    Published online by Cambridge University Press:
    30 January 2018, pp. 1189-1195
    Print publication:
    December 2014
    • Article
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  • This short note investigates convergence of adaptive Markov chain Monte Carlo algorithms, i.e. algorithms which modify the Markov chain update probabilities on the fly. We focus on the containment condition introduced Roberts and Rosenthal (2007). We show that if the containment condition is not satisfied, then the algorithm will perform very poorly. Specifically, with positive probability, the adaptive algorithm will be asymptotically less efficient then any nonadaptive ergodic MCMC algorithm. We call such algorithms AdapFail, and conclude that they should not be used.