research
∙
11/22/2022
A new and asymptotically optimally contracting coupling for the random walk Metropolis
The reflection-maximal coupling of the random walk Metropolis (RWM) algo...
share
research
∙
08/08/2022
SwISS: A Scalable Markov chain Monte Carlo Divide-and-Conquer Strategy
Divide-and-conquer strategies for Monte Carlo algorithms are an increasi...
research
∙
06/06/2022
Accelerating inference for stochastic kinetic models
Stochastic kinetic models (SKMs) are increasingly used to account for th...
research
∙
03/22/2022
Bounds on Wasserstein distances between continuous distributions using independent samples
The plug-in estimator of the Wasserstein distance is known to be conserv...
research
∙
12/15/2021
The Apogee to Apogee Path Sampler
Amongst Markov chain Monte Carlo algorithms, Hamiltonian Monte Carlo (HM...
research
∙
09/11/2020
Augmented pseudo-marginal Metropolis-Hastings for partially observed diffusion processes
We consider the problem of inference for nonlinear, multivariate diffusi...
research
∙
12/20/2019
Recruitment prediction for multi-centre clinical trials based on a hierarchical Poisson-gamma model: asymptotic analysis and improved intervals
We analyse predictions of future recruitment to a multi-centre clinical ...
research
∙
12/16/2019
Exact Bayesian inference for discretely observed Markov Jump Processes using finite rate matrices
We present new methodologies for Bayesian inference on the rate paramete...
research
∙
10/17/2019
Interim recruitment prediction for multi-centre clinical trials
We introduce a general framework for monitoring, modelling, and predicti...
research
∙
07/29/2019
Hug and Hop: a discrete-time, non-reversible Markov chain Monte Carlo algorithm
We introduced the Hug and Hop Markov chain Monte Carlo algorithm for est...
research
∙
01/10/2019
Inference for extreme values under threshold-based stopping rules
There is a propensity for an extreme value analyses to be conducted as a...
research
∙
09/19/2018
Efficient sampling of conditioned Markov jump processes
We consider the task of generating draws from a Markov jump process (MJP...
research
∙
09/19/2018
Simple, fast and accurate evaluation of the action of the exponential of a rate matrix on a probability vector
Given a time-homogeneous, finite-statespace Markov chain with a rate mat...
research
∙
09/06/2018
Reversible Markov chains: variational representations and ordering
This pedagogical document explains three variational representations tha...
research
∙
05/24/2018
Model-based inference of conditional extreme value distributions with hydrological applications
Multivariate extreme value models are used to estimate joint risk in a n...
research
∙
04/11/2018
Motor Unit Number Estimation via Sequential Monte Carlo
A change in the number of motor units that operate a particular muscle i...
research
∙
07/17/2017
A Discrete Bouncy Particle Sampler
Markov Chain Monte Carlo (MCMC) algorithms are statistical methods desig...
research
∙
05/27/2016
Merging MCMC Subposteriors through Gaussian-Process Approximations
Markov chain Monte Carlo (MCMC) algorithms have become powerful tools fo...
research
∙
12/23/2014