The Annals of Applied Probability
- Ann. Appl. Probab.
- Volume 29, Number 4 (2019), 2266-2301.
Ergodicity of the zigzag process
The zigzag process is a piecewise deterministic Markov process which can be used in a MCMC framework to sample from a given target distribution. We prove the convergence of this process to its target under very weak assumptions, and establish a central limit theorem for empirical averages under stronger assumptions on the decay of the target measure. We use the classical “Meyn–Tweedie” approach (Markov Chains and Stochastic Stability (2009) Cambridge Univ. Press; Adv. in Appl. Probab. 25 (1993) 487–517). The main difficulty turns out to be the proof that the process can indeed reach all the points in the space, even if we consider the minimal switching rates.
Ann. Appl. Probab., Volume 29, Number 4 (2019), 2266-2301.
Received: December 2017
Revised: October 2018
First available in Project Euclid: 23 July 2019
Permanent link to this document
Digital Object Identifier
Mathematical Reviews number (MathSciNet)
Zentralblatt MATH identifier
Bierkens, Joris; Roberts, Gareth O.; Zitt, Pierre-André. Ergodicity of the zigzag process. Ann. Appl. Probab. 29 (2019), no. 4, 2266--2301. doi:10.1214/18-AAP1453. https://projecteuclid.org/euclid.aoap/1563869043