Allen, M., Williams, M. D., Pitt, M., Stein, K., Worthington, D. and Suen, D. (2013). Managing emergency hospital admissions and beds: the impact of day-to-day variation by hospital size. In submission.
Bardwell, L., Eckley, I, Fearnhead, P., Smith, S. and Spott, M. (2016).Most recent changepoint detection in panel data. Submitted.
Bardwell, L. and Fearnhead, P. (2016).Bayesian detection of abnormal segments in multiple time series. To appear in Bayesian Analysis.
Barnett, H., Geys, H., Jacobs, T and Jaki, T. (2015). Multiple Comparisons of Model Averaged Derived Parameters with Applications to the Comparison of Sampling Methods in Pharmacokinetic Studies. In Submission.
Crespo Del Granado P., Pang Z. and Wallace S. W. (2016). Synergy of Smart grids and hybrid distributed generation on the value of energy storage, Applied Energy, forthcoming APEN_7540.
Crespo Del Granado P., Wallace S. W. and Pang Z. (2015). The impact of wind uncertainty on the strategic valuation of distributed electricity storage, Computational Management Science, Vol 13, 1, pp 5-27, DOI: 10.1007/s10287-015-0235-0.
Crespo Del Granado P., Wallace S. W. and Pang Z. (2014). The value of electricity storage in domestic homes: A smart grid perspective. Energy Systems, Vol 5, 2, pp 211-232,DOI: 10.1007/s12667-013-0108.
D. Nasiri (2014). Correlation Between Speeds on a Congested Road Network in the City of London. Submitted for publication. In Submission.
Edwards, J, Fearnhead, P. and Glazebrook, K. (2016).‘On the Identification and Mitigation of Weaknesses in the Knowledge Gradient Policy for Multi-Armed Bandits’, Probability in the Engineering and Informational Sciences, doi: 10.1017/S0269964816000279.
Fairbrother, J., Turner, A. and Wallace, S. (2015). Scenario generation for stochastic programs with tail risk measures. In Submission.
Fairbrother, J., Turner, A. and Wallace, S. (2015). Scenario generation for portfolio selection problems with tail risk measure. In Submission.
Haynes, K., Eckley, I. A., and Fearnhead, P., (2015). Computationally efficient changepoint detection for a range of penalties. Journal of Computational and Graphical Statistics (to appear).
Haynes, K., Fearnhead, P., and Eckley, I.A. (2015). A computationally efficient nonparametric approach for changepoint detection. To Appear in Statistics and Computing.
Hofmeyr, D. (2016) Clustering by minimum cut hyperplanes. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2016 (to appear)
Hofmeyr, D., Pavlidis, N., Eckley, I., (2015). Divisive clustering of high dimensional data streams. Statistics and Computing, doi: 10.1007/s11222-015-9597-y.
Hofmeyr, D., Pavlidis, N., Eckley, I., (2015)Minimum spectral connectivity projection pursuit for unsupervised classification. In Submission.
James, T., Glazebrook, K. D., Lin, K. (2014).Developing Effective Service Policies for Multiclass Queues with Abandonment: Asymptotic Optimality and Approximate Policy Improvement. INFORMS Journal of Computing, 28, 2, p. 251-264.
Kereszturi, M., Tawn, J. A. and Jonathan, P. (2015).Assessing extremal dependence of North Sea storm severity. Ocean Engineering, 118, 242-259.
Kereszturi, M., Tawn, J. A. (2016).Properties of extremal dependence models built on bivariate max-linearity. To Appear in J. Multivariate Analysis.
Letchford, A.N. and Nasiri, S.D. (2015).The Steiner travelling salesman problem with correlated costs. Eur. J. Oper. Res., 245(1), 62–69.
Letchford, A.N. and Nasiri, S.D. (2013).Pricing Routines for Vehicle Routing with Time Windows on Road Networks. Comput. & Oper. Res., 51, 331-337.
Letchford, A. N. & Nasiri, S. D. (2013).Compact formulations of the Steiner TSP and related problems. Eur. J. Oper. Res., 228, 83-92.
Ludkin, M., Eckley, I. and Neal, P. (2016).Dynamic stochastic block models - Parameter estimation and detection of changes in community structure. In Submission
Maidstone, R., Hocking, T., Rigaill, G., Fearnhead, P. (2014).On Optimal Multiple Changepoint Algorithms for Large Data. To Appear in Statistics and Computing.
Maidstone, R., Pickering, B. (2013).Comment on "Multiscale Change-Point Inference" by K. Frick, A. Munk and H. Sieling.
Malory, S., Sherlock, C.(2016).Residual-Bridge Constructs for Conditioned Diffusions. Submitted.
Nemeth, C., Fearnhead, P. and Mihaylova, L. (2013).“Sequential Monte Carlo Methods for State and Parameter Estimation in Abruptly Changing Environments”. IEEE Transactions on Signal Processing, Vol. 62, No. 5, pp. 1245-1255.
Nemeth, C., Fearnhead, P. and Mihaylova, L. (2016).Particle approximations of the score and observed information matrix for parameter estimation in state space models with linear computational cost. Journal of Computational and Graphical Statistics. 25, 1138-1157.
Nemeth, C.,Sherlock, C. and Fearnhead, P. (2016).Particle Metropolis-adjusted Langevin algorithms. Biometrika. 103, 701-717.
Palvidis, N., Hofmeyr, D., Tasoulis, S., (2015)Minimum density hyperplanes. Journal of Machine Learning Research, 17(156):1-33, 2016.
Park, T. Eckley, I. A. and Ombao H. C. (2013).Estimating time-evolving dependenc quantities between signals via multivariate locally stationary wavelet processes”, OEEE Transactions on Signal Processing, 62, 5240-5250.
Park, T., Eckley, I. A., and Ombao, H. (2015).Dynamic classification of multivariate time series using the multivariate locally stationary wavelet model (under revision).
Randell, D., Turnbull, K., Ewans, K., and Jonathan, P. (2015).Bayesian inference for non-stationary marginal extremes. In Submission.
Reeve, D.T., Randall, D., Ewans, K. C. and Jonathan, P. (2012).Uncertainty due to choice of measurement scale in Extreme Value modelling of North Sea Storm Severity. Ocean Engineering, 53, 164-176.
Rohrbeck, C., Costain, D and Frigessi, A. (2016).Bayesian Spatial Monotonic Multiple Regression. In submission.
Rohrbeck, C., Eastoe, E. F., Frigessi, A., and Tawn, J. A.(2016).Extreme Value Modelling of Water-related Insurance Claims. Submitted.
Ross, E., Kirkbride, C., Shakya, S. and Owusu, G. (2015).Cross-trained workforce planning for service industries: The effects of temporal demand flexibility. In submission.
Sharkey, P. and Tawn, J.A. (2016).A Poisson process reparameterisation for Bayesian inference for extremes. Extremes (to appear).
Turner, L., Dimitrov, N. and Fearnhead, P. (2016).Bayes linear methods for large-scale network search. Submitted.
Williamson, F., Jacko, P., Jaki, T. and Villar S. (2015).A Bayesian adaptive design for clinical trials in rare diseases. Computational Statistics & Data Analysis, DOI: 10.1016/j.csda.2016.09.006.
Winter, H. C. and Tawn, J. A. (2016).Modelling heatwaves in central France: a case study in extremal dependence. Journal of the Royal Statistical Society: Series C, 65(3), 345-365.
Winter, H. C., Tawn, J. A. and Brown, S. J. (2017).Detecting changing behaviour of heatwaves with climate change. Accepted for publication in Dynamics and Statistics of the Climate System.
Winter, H. C., Tawn, J. A. and Brown, S. J. (2016).Modelling the effect of the El Niño-Southern Oscillation on extreme spatial temperature events over Australia. Accepted for publication in The Annals of Applied Statistics.
Winter, H. C., Tawn, J. A. (2016). kth-order Markov models for assessing heatwave risks. Extremes. doi:10.1007/s10687-016-0275-z.
Yates, K., Pavlidis, N. and Hofmeyr, D. (2016).Density clustering for mixed and high-dimensional data. Submitted.
Briggs, K., Fairbrother, J. (2014). Enhanced algorithms for TV whitespace power maximization.
Davies, R., Mihaylova, L., Pavlidis, N. and Eckley, I.A. (2013). The effect of recovery algorithms on compressive sensing background subtraction” In Sensor Data Fusion: Trends, Solutions, Applications (SDF), 2013 Workshop on (pp. 1-6). IEEE.
Hofmeyr, D. (2016) On the topology of genetic algorithms. Proc. IJCAI (2016).
Hofmeyr, D. And Pavlidis, N. (2015)Maximum Clusterability Divisive Clustering. Proc. IEEE SSCI (CIDM)
Hofmeyr, D. And Pavlidis, N. (2015)Semi-supervised Spectral Connectivity Projection Pursuit. Proc. PRASA RobMech Int. Conf.
Morgan, L. E., Nelson, B. L., Worthington, D. and Titman, A. (2016).“Input Uncertainty Quantification for Simulation Models with Piecewise-Constant Non-Stationary Poisson Arrival Processes” The Winter Simulation Conference 2016
Nemeth, C., Fearnhead, P., Mihaylova, L. and Vorley, D. (2012).“Particle learning for state and parameter estimation,” 9Th IET Data Fusion and Target Tracking Conference (DF&TT 2012), London U.K.
Nemeth, C., Fearnhead, P., Mihaylova, L. and Vorley, D. (2012).“Bearings-Only Tracking with Particle Filtering for Joint Parameter and State Estimation,” 15Th International Conference on Information Fusion, pp. 824-831.
Pike-Burke, C., Grünewälder, S. (2017)."Optimistic Planning for the Stochastic Knapsack Problem," in Proceedings of 20th International Conference on Artificial Intelligence and Statistics
Randell, D., Zanini, E., Vogel, M., Ewans, K., Jonathan, P. (2014).“Omnidirectional Return values for Storm Severity from Directional Extreme Values Models: The Effect of Physical Environment and Sample Size. Proceedings of 33nd International Conference on Ocean, Offshore and Arctic Engineering, San Francisco OMAE2014-23156.
Yates, K. and Pavlidis, N. (2016).Minimum density hyperplanes in the feature space. Advances in High Dimensional Big Data" workshop, IEEE international conference on Big Data, Washington.