Invited comment on the paper "Slice Sampling" by Radford Neal

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PyMC: a modern, and comprehensive probabilistic programming framework in Python (2023, methodology): “Other available inference methods include random-walk Metropolis (including specialized versions for binary and categorical parameters), a slice sampler ( Neal, 2003 ), and Differential Evolution Metropolis sampling ( Ter Braak, 2006 ).”
dynesty: a dynamic nested sampling package for estimating Bayesian posteriors and evidences (2019, methodology): “These are based on the “stepping out” method proposed in Neal (2003) and Jasa & Xiang (2012), which works as follows in the single-variable case starting from the position xk of the kth live point: (i) Draw a standard uniform random number U. (ii) Set the left bound L = xk − wU and the right as R =…”