166 citations · 615 across the 26 of their papers we have counts for
35 papers
Robust, partially alive particle Metropolis-Hastings via the Frankenfilter
Chris Sherlock, Andrew Golightly, Anthony Lee
When a hidden Markov model permits the conditional likelihood of an observation given the hidden process to be zero, all particle simulations from one observation time to the next…
Nested ensemble Kalman filter for static parameter inference in nonlinear state-space models
Andrew Golightly, Sarah E. Heaps, Chris Sherlock +2
The ensemble Kalman filter (EnKF) is a popular technique for performing inference in state-space models (SSMs), particularly when the dynamic process is high-dimensional. Unlike re…
Variance bounds and robust tuning for pseudo-marginal Metropolis--Hastings algorithms
Chris Sherlock
The general applicability and ease of use of the pseudo-marginal Metropolis--Hastings (PMMH) algorithm, and particle Metropolis--Hastings in particular, makes it a popular method f…
Scalable couplings for the random walk Metropolis algorithm
Tamás P. Papp, Chris Sherlock
There has been a recent surge of interest in coupling methods for Markov chain Monte Carlo algorithms: they facilitate convergence quantification and unbiased estimation, while exp…
Accelerating inference for stochastic kinetic models
Tom E. Lowe, Andrew Golightly, Chris Sherlock
Stochastic kinetic models (SKMs) are increasingly used to account for the inherent stochasticity exhibited by interacting populations of species in areas such as epidemiology, popu…
Centered plug-in estimation of Wasserstein distances
Tamás P. Papp, Chris Sherlock
The plug-in estimator of the squared Euclidean 2-Wasserstein distance is conservative, however due to its large positive bias it is often uninformative. We eliminate most of this b…