Outputs (44)

Standardised profiling for tinnitus research: the European School for Interdisciplinary Tinnitus Research Screening Questionnaire (ESIT-SQ) (2019)
Journal Article
Genitsaridi, E., Partyka, M., Gallus, S., Lopez-Escamez, J. A., Schecklmann, M., Mielczarek, M., Trpchevska, N., Santacruz, J. L., Schoisswohl, S., Riha, C., Lourenco, M., Biswas, R., Liyanage, N., Cederroth, C. R., Perez-Carpena, P., Devos, J., Fuller, T., Edvall, N. K., Hellberg, M. P., D'Antonio, A., …Hall, D. A. (2019). Standardised profiling for tinnitus research: the European School for Interdisciplinary Tinnitus Research Screening Questionnaire (ESIT-SQ). Hearing Research, 377, 353-359. https://doi.org/10.1016/j.heares.2019.02.017

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
Alharthi, M., Kypraios, T., & O'Neill, P. D. (2019). Bayes Factors for Partially Observed Stochastic Epidemic Models. Bayesian Analysis, 14(3), 927-956. https://doi.org/10.1214/18-BA1134

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
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 modelling framework for the spread of nosocomial infections (2018)
Journal Article
López-García, M., & Kypraios, T. (2018). A unified stochastic modelling framework for the spread of nosocomial infections. Interface, 15(143), Article 20180060. 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 modelling 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., Kypraios, T., Scott, D. J., Hill, P. J., & 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.

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.