Bayesian methods

Slice Sampling

Slice sampling is a Markov chain Monte Carlo (MCMC) algorithm introduced by Radford M. Neal in his 2003 Annals of Statistics paper. It generates samples from a target distribution by drawing uniformly from the region under the density curve — called the 'slice' — without requiring the user to specify a step-size or proposal distribution, making it self-tuning and broadly applicable for Bayesian posterior inference.

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Sources

  1. Neal, R. M. (2003). Slice sampling (with discussion). Annals of Statistics, 31(3), 705–767. DOI: 10.1214/aos/1056562461
  2. Gelman, A., Carlin, J. B., Stern, H. S., Dunson, D. B., Vehtari, A., & Rubin, D. B. (2013). Bayesian Data Analysis (3rd ed.). CRC Press. ISBN: 978-1439840955
  3. Robert, C. P., & Casella, G. (2004). Monte Carlo Statistical Methods (2nd ed.). Springer. ISBN: 978-0387212395

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Referenced by

ScholarGateSlice Sampling (Slice Sampling MCMC). Retrieved 2026-06-04 from https://scholargate.app/en/bayesian/slice-sampling