Abstract
Based on a new coupling approach, we prove that the transition step of the Hamiltonian Monte Carlo algorithm is contractive w.r.t. a carefully designed Kantorovich (L1 Wasserstein) distance. The lower bound for the contraction rate is explicit. Global convexity of the potential is not required, and thus multimodal target distributions are included. Explicit quantitative bounds for the number of steps required to approximate the stationary distribution up to a given error ϵ are a direct consequence of contractivity. These bounds show that HMC can overcome diffusive behavior if the duration of the Hamiltonian dynamics is adjusted appropriately.
Original language | English (US) |
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Pages (from-to) | 1209-1250 |
Number of pages | 42 |
Journal | Annals of Applied Probability |
Volume | 30 |
Issue number | 3 |
DOIs | |
State | Published - Jun 2020 |
All Science Journal Classification (ASJC) codes
- Statistics and Probability
- Statistics, Probability and Uncertainty
Keywords
- Convergence to equilibrium
- Coupling
- Geometric integration
- Hamiltonian Monte Carlo
- Hybrid Monte Carlo
- Markov chain Monte Carlo
- Metropolis-Hastings