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stat.CO2025
Sampling with time-changed Markov processes
Andrea Bertazzi, Giorgos Vasdekis
We study time-changed Markov processes to speed up the convergence of Markov chain Monte Carlo (MCMC) algorithms. The time-changed process is defined by adjusting the speed of time…
stat.CO2020
Adaptive schemes for piecewise deterministic Monte Carlo algorithms
Andrea Bertazzi, Joris Bierkens
The Bouncy Particle sampler (BPS) and the Zig-Zag sampler (ZZS) are continuous time, non-reversible Monte Carlo methods based on piecewise deterministic Markov processes. Experimen…