Skip to main content

Research Repository

Advanced Search

All Outputs (43)

Optimal experimental design for predator–prey functional response experiments (2018)
Journal Article
Zhang, J. F., Papanikolaou, N. E., Kypraios, T., & Drovandi, C. C. (2018). Optimal experimental design for predator–prey functional response experiments. Interface, 15(144), https://doi.org/10.1098/rsif.2018.0186

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 modeling framework for the spread of nosocomial infections (2018)
Journal Article
López-García, M., & Kypraios, T. (2018). A unified stochastic modeling framework for the spread of nosocomial infections. Interface, 15(143), https://doi.org/10.1098/rsif.2018.0060

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 modeling framework for the spread of nosocomial infections.

Bayesian nonparametrics for stochastic epidemic models (2018)
Journal Article
Kypraios, T., & O'Neill, P. D. (2018). Bayesian nonparametrics for stochastic epidemic models. Statistical Science, 33(1), https://doi.org/10.1214/17-STS617

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
Golightly, A., & Kypraios, T. (2018). Efficient SMC2 schemes for stochastic kinetic models. Statistics and Computing, 28(6), 1215-1230. https://doi.org/10.1007/s11222-017-9789-8

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
Pérez López, I., Hodge, D., & Kypraios, T. (2018). Auxiliary variables for Bayesian inference in multi-class queueing networks. Statistics and Computing, 28(6), 1187-1200. https://doi.org/10.1007/s11222-017-9787-x

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
Iqbal, M., Doherty, N., Page, A. M., Qazi, S. N., Ajmera, I., Lund, P. A., …Stekel, D. J. (2017). Reconstructing promoter activity from Lux bioluminescent reporters. PLoS Computational Biology, 13(9), Article e1005731. https://doi.org/10.1371/journal.pcbi.1005731

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
Prangle, D., Everitt, R. G., & Kypraios, T. (in press). A rare event approach to high-dimensional approximate Bayesian computation. Statistics and Computing, 28(4), https://doi.org/10.1007/s11222-017-9764-4

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
Boehm-Sturm, P., Füchtemeier, M., Foddis, M., Mueller, S., Trueman, R. C., Zille, M., …Farr, T. D. (in press). Neuroimaging biomarkers predict brain structural connectivity change in a mouse model of vascular cognitive impairment. Stroke, 48(1), https://doi.org/10.1161/STROKEAHA.116.014394

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
Stockdale, J. E., Kypraios, T., & O’Neill, P. D. (2017). Modelling and Bayesian analysis of the Abakaliki smallpox data. Epidemics, 19, https://doi.org/10.1016/j.epidem.2016.11.005

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
Down, P., Bradley, A., Breen, J., Browne, W., Kypraios, T., & Green, M. (2016). A Bayesian micro-simulation to evaluate the cost-effectiveness of interventions for mastitis control during the dry period in UK dairy herds. Preventive Veterinary Medicine, 133, 64-72. https://doi.org/10.1016/j.prevetmed.2016.09.012

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
Kypraios, T., Neal, P., & Prangle, D. (2017). A tutorial introduction to Bayesian inference for stochastic epidemic models using Approximate Bayesian Computation. Mathematical Biosciences, 287, https://doi.org/10.1016/j.mbs.2016.07.001

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
Papanikolaou, N., Williams, H., Demiris, N., Preston, S., Milonas, P., & Kypraios, T. (2016). Bayesian inference and model choice for Holling’s disc equation: a case study on an insect predator-prey system. Community Ecology, 17(1), 71-78. https://doi.org/10.1556/168.2016.17.1.9

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.

Statistically efficient tomography of low rank states with incomplete measurements (2016)
Journal Article
Acharya, A., Kypraios, T., & Gut?a?, M. (2016). Statistically efficient tomography of low rank states with incomplete measurements. New Journal of Physics, 18(4), https://doi.org/10.1088/1367-2630/18/4/043018

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
Worby, C. J., O'Neill, P. D., Kypraios, T., Robotham, J. V., De Angelis, D., Cartwright, E. J., …Cooper, B. S. (2016). Reconstructing transmission trees for communicable diseases using densely sampled genetic data. Annals of Applied Statistics, 10(1), https://doi.org/10.1214/15-AOAS898

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
Xu, X., Kypraios, T., & O'Neill, P. D. (2016). Bayesian non-parametric inference for stochastic epidemic models using Gaussian Processes. Biostatistics, 17(4), 619-633. https://doi.org/10.1093/biostatistics/kxw011

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
Gerstgrasser, M., Nicholls, S., Stout, M., Smart, K., Powell, C., Kypraios, T., & Stekel, D. J. (2016). A Bayesian approach to analyzing phenotype microarray data enables estimation of microbial growth parameters. Journal of Bioinformatics and Computational Biology, 14(03), 1-23. https://doi.org/10.1142/S0219720016500074

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
Fallaize, C. J., & Kypraios, T. (in press). Exact Bayesian inference for the Bingham distribution. Statistics and Computing, 26(1), https://doi.org/10.1007/s11222-014-9508-7

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.

Spectral thresholding quantum tomography for low rank states (2015)
Journal Article
Butucea, C., Gu??, M., & Kypraios, T. (2015). Spectral thresholding quantum tomography for low rank states. New Journal of Physics, 17(11), Article 113050. https://doi.org/10.1088/1367-2630/17/11/113050

The estimation of high dimensional quantum states is an important statistical problem arising in current quantum technology applications. A key example is the tomography of multiple ions states, employed in the validation of state preparation in ion... Read More about Spectral thresholding quantum tomography for low rank states.

On the epidemic of financial crises (2013)
Journal Article
Demiris, N., Kypraios, T., & Smith, L. V. (2014). On the epidemic of financial crises. Journal of the Royal Statistical Society: Series A, 177(3), 697-723. https://doi.org/10.1111/rssa.12044

The paper proposes a framework for modelling financial contagion that is based on susceptible-infected-recovered transmission models from epidemic theory. This class of models addresses two important features of contagion modelling, which are a commo... Read More about On the epidemic of financial crises.