4 citations · 10 across the 7 of their papers we have counts for
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Counterexamples for optimal scaling of Metropolis-Hastings chains with rough target densities
Jure Vogrinc, Wilfrid Stephen Kendall
For sufficiently smooth targets of product form it is known that the variance of a single coordinate of the proposal in RWM (Random walk Metropolis) and MALA (Metropolis adjusted L…
A Metropolis-class sampler for targets with non-convex support
John Moriarty, Jure Vogrinc, Alessandro Zocca
We aim to improve upon the exploration of the general-purpose random walk Metropolis algorithm when the target has non-convex support , by reusing proposals…
Asymptotic variance for Random walk Metropolis chains in high dimensions: logarithmic growth via the Poisson equation
Aleksandar Mijatović, Jure Vogrinc
There are two ways of speeding up MCMC algorithms: (1) construct more complex samplers that use gradient and higher order information about the target and (2) design a control vari…
On the Poisson equation for Metropolis-Hastings chains
Aleksandar Mijatovic, Jure Vogrinc
This paper defines an approximation scheme for a solution of the Poisson equation of a geometrically ergodic Metropolis-Hastings chain . The approximations give rise to a natura…