5 papers
Pathwise skew-symmetric discretisation for SDEs with superlinear drift
Yuga Iguchi, Samuel Livingstone, Giorgos Vasdekis +1
The skew-symmetric discretisation has recently been proposed as a new robust simulation method for weakly approximating stochastic differential equations (SDEs) with non-globally L…
On randomized step sizes in Metropolis-Hastings algorithms
Sebastiano Grazzi, Samuel Livingstone, Lionel Riou-Durand
The performance of Metropolis-Hastings algorithms is highly sensitive to the choice of step size, and miss-specification can lead to severe loss of efficiency. We study algorithms…
Skew-symmetric schemes for stochastic differential equations with non-Lipschitz drift: an unadjusted Barker algorithm
Yuga Iguchi, Samuel Livingstone, Nikolas Nüsken +2
We propose a new simple and explicit numerical scheme for time-homogeneous stochastic differential equations. The scheme is based on sampling increments at each time step from a sk…
Foundations of locally-balanced Markov processes
Samuel Livingstone, Giorgos Vasdekis, Giacomo Zanella
We formally introduce and study locally-balanced Markov jump processes (LBMJPs) defined on a general state space. These continuous-time stochastic processes with a user-specified l…
Quantifying the effectiveness of linear preconditioning in Markov chain Monte Carlo
Max Hird, Samuel Livingstone
We study linear preconditioning in Markov chain Monte Carlo. We consider the class of well-conditioned distributions, for which several mixing time bounds depend on the condition n…