Adaptive Rejection Sampling for Gibbs Sampling

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ID: 291612
1992
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Ranked #3 of 46 articles by views in Journal of the Royal Statistical Society Series C (Applied Statistics)

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Abstract
We propose a method for rejection sampling from any univariate log‐concave probability density function. The method is adaptive: As sampling proceeds, the rejection envelope and the squeezing function converge to the density function. The rejection envelope and squeezing function are piece‐wise exponential functions, the rejection envelope touching the density at previously sampled points, and the squeezing function forming arcs between those points of contact. The technique is intended for situations where evaluation of the density is computationally expensive, in particular for applications of Gibbs sampling to Bayesian models with non‐conjugacy. We apply the technique to a Gibbs sampling analysis of monoclonal antibody reactivity.
Reference Key
openalex_W2204383650 Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Walter R. Gilks, Pascal Wild
Journal Journal of the Royal Statistical Society Series C (Applied Statistics)
Year 1992
DOI
10.2307/2347565
URL
https://doi.org/10.2307/2347565
Keywords Keywords not found

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