All Outputs (45)

Standardised profiling for tinnitus research: the European School for Interdisciplinary Tinnitus Research Screening Questionnaire (ESIT-SQ) (2019)
Journal Article

Background The heterogeneity of tinnitus is substantial. Its numerous pathophysiological mechanisms and clinical manifestations have hampered fundamental and treatment research significantly. A decade ago, the Tinnitus Research Initiative introduced... Read More about Standardised profiling for tinnitus research: the European School for Interdisciplinary Tinnitus Research Screening Questionnaire (ESIT-SQ).

Bayes Factors for Partially Observed Stochastic Epidemic Models (2018)
Journal Article

We consider the problem of model choice for stochastic epidemic models given partial observation of a disease outbreak through time. Our main focus is on the use of Bayes factors. Although Bayes factors have appeared in the epidemic modelling literat... Read More about Bayes Factors for Partially Observed Stochastic Epidemic Models.

Optimal experimental design for predator–prey functional response experiments (2018)
Journal Article

Functional response models are important in understanding predator–prey interactions. The development of functional response methodology has progressed from mechanistic models to more statistically motivated models that can account for variance and t... Read More about Optimal experimental design for predator–prey functional response experiments.

A unified stochastic modelling framework for the spread of nosocomial infections (2018)
Journal Article

Over the last years, a number of stochastic models have been proposed for analysing the spread of nosocomial infections in hospital settings. These models often account for a number of factors governing the spread dynamics: spontaneous patient coloni... Read More about A unified stochastic modelling framework for the spread of nosocomial infections.

Bayesian nonparametrics for stochastic epidemic models (2018)
Journal Article

The vast majority of models for the spread of communicable diseases are parametric in nature and involve underlying assumptions about how the disease spreads through a population. In this article we consider the use of Bayesian nonparametric approach... Read More about Bayesian nonparametrics for stochastic epidemic models.

Efficient SMC2 schemes for stochastic kinetic models (2017)
Journal Article

Fitting stochastic kinetic models represented by Markov jump processes within the Bayesian paradigm is complicated by the intractability of the observed-data likelihood. There has therefore been considerable attention given to the design of pseudo-ma... Read More about Efficient SMC2 schemes for stochastic kinetic models.

Auxiliary variables for Bayesian inference in multi-class queueing networks (2017)
Journal Article

Queueing networks describe complex stochastic systems of both theoretical and practical interest. They provide the means to assess alterations, diagnose poor performance and evaluate robustness across sets of interconnected resources. In the present... Read More about Auxiliary variables for Bayesian inference in multi-class queueing networks.

Reconstructing promoter activity from Lux bioluminescent reporters (2017)
Journal Article

The bacterial Lux system is used as a gene expression reporter. It is fast, sensitive and non-destructive, enabling high frequency measurements. Originally developed for bacterial cells, it has also been adapted for eukaryotic cells, and can be used... Read More about Reconstructing promoter activity from Lux bioluminescent reporters.

A rare event approach to high-dimensional approximate Bayesian computation (2017)
Journal Article

Approximate Bayesian computation (ABC) methods permit approximate inference for intractable likelihoods when it is possible to simulate from the model. However they perform poorly for high dimensional data, and in practice must usually be used in con... Read More about A rare event approach to high-dimensional approximate Bayesian computation.

Neuroimaging biomarkers predict brain structural connectivity change in a mouse model of vascular cognitive impairment (2017)
Journal Article

Background and Purpose�Chronic hypoperfusion in the mouse brain has been suggested to mimic aspects of vascular cognitive impairment, such as white matter damage. Although this model has attracted attention, our group has struggled to generate a reli... Read More about Neuroimaging biomarkers predict brain structural connectivity change in a mouse model of vascular cognitive impairment.

Modelling and Bayesian analysis of the Abakaliki smallpox data (2016)
Journal Article

The celebrated Abakaliki smallpox data have appeared numerous times in the epidemic modelling literature, but in almost all cases only a specific subset of the data is considered. The only previous analysis of the full data set relied on approximatio... Read More about Modelling and Bayesian analysis of the Abakaliki smallpox data.

A Bayesian micro-simulation to evaluate the cost-effectiveness of interventions for mastitis control during the dry period in UK dairy herds (2016)
Journal Article

Importance of the dry period with respect to mastitis control is now well established although the precise interventions that reduce the risk of acquiring intramammary infections during this time are not clearly understood. There are very few interve... Read More about A Bayesian micro-simulation to evaluate the cost-effectiveness of interventions for mastitis control during the dry period in UK dairy herds.

A tutorial introduction to Bayesian inference for stochastic epidemic models using Approximate Bayesian Computation (2016)
Journal Article

Likelihood-based inference for disease outbreak data can be very challenging due to the inherent dependence of the data and the fact that they are usually incomplete. In this paper we review recent Approximate Bayesian Computation (ABC) methods for t... Read More about A tutorial introduction to Bayesian inference for stochastic epidemic models using Approximate Bayesian Computation.

Bayesian inference and model choice for Holling’s disc equation: a case study on an insect predator-prey system (2016)
Journal Article

The dynamics of predator-prey systems relate strongly to the density (in)dependent attributes of the predator’s feeding rate, i.e., its functional response. The outcome of functional response models is often used in theoretical or applied ecology in... Read More about Bayesian inference and model choice for Holling’s disc equation: a case study on an insect predator-prey system.

Corrigendum: Spectral thresholding quantum tomography for low rank states (2015 New J. Phys. 17 113050) (2016)
Journal Article

Statistically efficient tomography of low rank states with incomplete measurements (2016)
Journal Article

The construction of physically relevant low dimensional state models, and the design of appropriate measurements are key issues in tackling quantum state tomography for large dimensional systems. We consider the statistical problem of estimating low... Read More about Statistically efficient tomography of low rank states with incomplete measurements.

Reconstructing transmission trees for communicable diseases using densely sampled genetic data (2016)
Journal Article

Whole genome sequencing of pathogens from multiple hosts in an epidemic offers the potential to investigate who infected whom with unparalleled resolution, potentially yielding important insights into disease dynamics and the impact of control measur... Read More about Reconstructing transmission trees for communicable diseases using densely sampled genetic data.

Bayesian non-parametric inference for stochastic epidemic models using Gaussian Processes (2016)
Journal Article

This paper considers novel Bayesian non-parametric methods for stochastic epidemic models. Many standard modeling and data analysis methods use underlying assumptions (e.g. concerning the rate at which new cases of disease will occur) which are rarel... Read More about Bayesian non-parametric inference for stochastic epidemic models using Gaussian Processes.

A Bayesian approach to analyzing phenotype microarray data enables estimation of microbial growth parameters (2016)
Journal Article

Biolog phenotype microarrays enable simultaneous, high throughput analysis of cell cultures in different environments. The output is high-density time-course data showing redox curves (approximating growth) for each experimental condition. The softwa... Read More about A Bayesian approach to analyzing phenotype microarray data enables estimation of microbial growth parameters.

Exact Bayesian inference for the Bingham distribution (2016)
Journal Article

This paper is concerned with making Bayesian inference from data that are assumed to be drawn from a Bingham distribution. A barrier to the Bayesian approach is the parameter-dependent normalising constant of the Bingham distribution, which, even whe... Read More about Exact Bayesian inference for the Bingham distribution.