58 citations · 148 across the 25 of their papers we have counts for
28 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…
Sequential Bayesian inference for stochastic epidemic models of cumulative incidence
Sam A. Whitaker, Andrew Golightly, Colin S. Gillespie +1
Epidemics are inherently stochastic, and stochastic models provide an appropriate way to describe and analyse such phenomena. Given temporal incidence data consisting of, for examp…
Using extreme value theory to evaluate the leading pedestrian interval road safety intervention
Nicola Hewett, Lee Fawcett, Andrew Golightly +1
Improving road safety is hugely important with the number of deaths on the world's roads remaining unacceptably high; an estimated 1.35 million people die each year as a result of…
Accelerating Bayesian inference for stochastic epidemic models using incidence data
Andrew Golightly, Laura E. Wadkin, Sam A. Whitaker +3
We consider the case of performing Bayesian inference for stochastic epidemic compartment models, using incomplete time course data consisting of incidence counts that are either t…
Bayesian inference for a spatio-temporal model of road traffic collision data
Nicola Hewett, Andrew Golightly, Lee Fawcett +1
Improving road safety is hugely important with the number of deaths on the world's roads remaining unacceptably high; an estimated 1.35 million people die each year (WHO, 2020). Cu…
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…