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Slow hit-and-run sampling

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  • Bélisle, Claude

Abstract

We show that the hit-and-run sampler can converge to its target distribution at an arbitrarily slow rate. We also illustrate how the speed of convergence of the hit-and-run sampler can be affected by small perturbations of the target distribution.

Suggested Citation

  • Bélisle, Claude, 2000. "Slow hit-and-run sampling," Statistics & Probability Letters, Elsevier, vol. 47(1), pages 33-43, March.
    • Handle: RePEc:eee:stapro:v:47:y:2000:i:1:p:33-43
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    References listed on IDEAS

    as
    1. Robert L. Smith, 1984. "Efficient Monte Carlo Procedures for Generating Points Uniformly Distributed over Bounded Regions," Operations Research, INFORMS, vol. 32(6), pages 1296-1308, December.
    2. Claude J. P. Bélisle & H. Edwin Romeijn & Robert L. Smith, 1993. "Hit-and-Run Algorithms for Generating Multivariate Distributions," Mathematics of Operations Research, INFORMS, vol. 18(2), pages 255-266, May.
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