
Augmented pseudomarginal MetropolisHastings for partially observed diffusion processes
We consider the problem of inference for nonlinear, multivariate diffusi...
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Recruitment prediction for multicentre clinical trials based on a hierarchical Poissongamma model: asymptotic analysis and improved intervals
We analyse predictions of future recruitment to a multicentre clinical ...
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Exact Bayesian inference for discretely observed Markov Jump Processes using finite rate matrices
We present new methodologies for Bayesian inference on the rate paramete...
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Interim recruitment prediction for multicentre clinical trials
We introduce a general framework for monitoring, modelling, and predicti...
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Hug and Hop: a discretetime, nonreversible Markov chain Monte Carlo algorithm
We introduced the Hug and Hop Markov chain Monte Carlo algorithm for est...
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Inference for extreme values under thresholdbased stopping rules
There is a propensity for an extreme value analyses to be conducted as a...
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Efficient sampling of conditioned Markov jump processes
We consider the task of generating draws from a Markov jump process (MJP...
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Simple, fast and accurate evaluation of the action of the exponential of a rate matrix on a probability vector
Given a timehomogeneous, finitestatespace Markov chain with a rate mat...
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Reversible Markov chains: variational representations and ordering
This pedagogical document explains three variational representations tha...
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Modelbased inference of conditional extreme value distributions with hydrological applications
Multivariate extreme value models are used to estimate joint risk in a n...
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Motor Unit Number Estimation via Sequential Monte Carlo
A change in the number of motor units that operate a particular muscle i...
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A Discrete Bouncy Particle Sampler
Markov Chain Monte Carlo (MCMC) algorithms are statistical methods desig...
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Merging MCMC Subposteriors through GaussianProcess Approximations
Markov chain Monte Carlo (MCMC) algorithms have become powerful tools fo...
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Particle Metropolisadjusted Langevin algorithms
This paper proposes a new sampling scheme based on Langevin dynamics tha...
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Chris Sherlock
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