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A latent slice sampling algorithm

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  • Li, Yanxin
  • Walker, Stephen G.

Abstract

Motivated by a sampling algorithm for discrete spaces, a variation of the slice sampler for continuous spaces is introduced. It utilizes latent variables and is related to Neal's slice sampler. The key difference is that the additional latent variables allow the sequential stepping out or doubling procedures, which makes the basic slice sampler difficult to use in high dimensional problems, to be avoided. On the other hand, the latent slice sampling algorithm is applicable on high dimensional problems where the variables can all be treated in a single block.

Suggested Citation

  • Li, Yanxin & Walker, Stephen G., 2023. "A latent slice sampling algorithm," Computational Statistics & Data Analysis, Elsevier, vol. 179(C).
    • Handle: RePEc:eee:csdana:v:179:y:2023:i:c:s0167947322002328
    DOI: 10.1016/j.csda.2022.107652
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    References listed on IDEAS

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    Cited by:

    1. Han Cheng Lie & Daniel Rudolf & Björn Sprungk & T. J. Sullivan, 2023. "Dimension‐independent Markov chain Monte Carlo on the sphere," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 50(4), pages 1818-1858, December.

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