All Outputs (43)

Piecewise Approximate Bayesian Computation: fast inference for discretely observed Markov models using a factorised posterior distribution (2013)
Journal Article
White, S. R., Kypraios, T., & Preston, S. P. (2015). Piecewise Approximate Bayesian Computation: fast inference for discretely observed Markov models using a factorised posterior distribution. Statistics and Computing, 25(2), 289-301. https://doi.org/10.1007/s11222-013-9432-2

© 2013, The Author(s). Many modern statistical applications involve inference for complicated stochastic models for which the likelihood function is difficult or even impossible to calculate, and hence conventional likelihood-based inferential techni... Read More about Piecewise Approximate Bayesian Computation: fast inference for discretely observed Markov models using a factorised posterior distribution.

Rank-based model selection for multiple ions quantum tomography (2012)
Journal Article
Gu??, M., Kypraios, T., & Dryden, I. (2012). Rank-based model selection for multiple ions quantum tomography. New Journal of Physics, 14(105002), https://doi.org/10.1088/1367-2630/14/10/105002

The statistical analysis of measurement data has become a key component of many quantum engineering experiments. As standard full state tomography becomes unfeasible for large dimensional quantum systems, one needs to exploit prior information and th... Read More about Rank-based model selection for multiple ions quantum tomography.

Bayesian model choice via mixture distributions with application to epidemics and population process models
Book
O'Neill, P. D., & Kypraios, T. Bayesian model choice via mixture distributions with application to epidemics and population process models. University of Nottingham

We consider Bayesian model choice for the setting where the observed data are partially observed realisations of a stochastic population process. A new method for computing Bayes factors is described which avoids the need to use reversible jump appro... Read More about Bayesian model choice via mixture distributions with application to epidemics and population process models.