A Note on the Polynomial Ergodicity of the One-Dimensional Zig-Zag process
G. Vasdekis, G. O. Roberts

TL;DR
This paper establishes polynomial ergodicity for the one-dimensional Zig-Zag process on heavy-tailed distributions, specifically identifying the precise polynomial rate of convergence for Student distributions.
Contribution
It provides the first rigorous proof of polynomial ergodicity for the Zig-Zag process on heavy-tailed targets and determines the exact convergence order for Student distributions.
Findings
Proves polynomial ergodicity for heavy-tailed targets.
Identifies the exact polynomial convergence rate for Student distributions.
Enhances understanding of Zig-Zag process behavior on complex distributions.
Abstract
We prove polynomial ergodicity for the one-dimensional Zig-Zag process on heavy tailed targets and identify the exact order of polynomial convergence of the process when targeting Student distributions.
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Taxonomy
TopicsStochastic processes and statistical mechanics · Markov Chains and Monte Carlo Methods · Bayesian Methods and Mixture Models
