Reversibility of elliptical slice sampling revisited
Not on the map. Why?
Abstract (arXiv)
We extend elliptical slice sampling, a Markov chain transition kernel suggested in Murray, Adams and MacKay 2010, to infinite-dimensional separable Hilbert spaces and discuss its well-definedness. We point to a regularity requirement, provide an alternative proof of the desirable reversibility property and show that it induces a positive semi-definite Markov operator. Crucial within the proof of the formerly mentioned results is the analysis of a shrinkage Markov chain that may be interesting on its own.
Key facts. Cited by 3 papers in the map (data through 7 Oct 2026). Builds on 6 of its 37 references that are in the map. First posted on arXiv 6 Jan 2023.
Builds on
6 of 37 references.
References · 6
- 2014Dimension-independent likelihood-informed MCMCcited by 36
- 2015Perturbation theory for Markov chains via Wasserstein distancecited by 16
- 2019Integrals over Gaussians under Linear Domain Constraintscited by 15
- 2021Geometric convergence of elliptical slice samplingcited by 5
- 2014Convergence of hybrid slice sampling via spectral gapcited by 4
- 2019Efficient Bayesian shape-restricted function estimation with constrained Gaussian process priorscited by 3
Built on by
Citing papers per year: 2023: 1; 2024: 1; 2025: 1.
3 papers.