ACEMS Publications

Rebuli, N. P., Bean N. G., & Ross J. V. (2017).  Hybrid Markov chain models of S–I–R disease dynamics. Journal of Mathematical Biology. doi: 10.1007/s00285-016-1085-2
Feng, L.B., Zhuang P., Liu F., Turner I., & Li J. (2017).  High-order numerical methods for the Riesz space fractional advection–dispersion equations. Computers & Mathematics with Applications. doi: 10.1016/j.camwa.2016.01.015
Feng, G., Gao J., Peng B., & Zhang X. (2017).  A varying-coefficient panel data model with fixed effects: Theory and an application to US commercial banks. Journal of Econometrics. 196(1), 68-82. doi: 10.1016/j.jeconom.2016.09.011
Tredenick, E. C., Farrell T., W. Forster A., & Psaltis S. T. P. (2017).  Nonlinear Porous Diffusion Modeling of Hydrophilic Ionic Agrochemicals in Astomatous Plant Cuticle Aqueous Pores: A Mechanistic Approach. Frontiers in Plant Science. 8, doi: 10.3389/fpls.2017.00746
Mengersen, K., Peterson E. E., Clifford S., Ye N., Kim J., Bednarz T., et al. (2017).  Modelling imperfect presence data obtained by citizen science. Environmetrics. 28(5), e2446. doi: 10.1002/env.v28.5,10.1002/env.2446
Lee, J., Brown J., & Ryan L. M. (2017).  Sufficiency revisited: Rethinking statistical algorithms in the big data era. The American Statistician. doi: 10.1080/00031305.2016.1255659
Andersen, L. Nørvang, Laub P., & Rojas-Nandayapa L. (2017).  Efficient Simulation for Dependent Rare Events with Applications to Extremes. Methodology and Computing in Applied Probability. doi: 10.1007/s11009-017-9557-4
Ma, Y., Liu A., Egodawatta P., McGree J., & Goonetilleke A. (2017).  Assessment and management of human health risk from toxic metals and polycyclic aromatic hydrocarbons in urban stormwater arising from anthropogenic activities and traffic congestion. Science of The Total Environment. 202-211. doi: 10.1016/j.scitotenv.2016.11.015
Cusimano, N., Burrage K., Turner I., & Kay D. (2017).  On reflecting boundary conditions for space-fractional equations on a finite interval: Proof of the matrix transfer technique. Applied Mathematical Modelling. 554-565. doi: 10.1016/j.apm.2016.10.021
Anderson, C., Lee D., & Dean N. (2017).  Spatial clustering of average risks and risk trends in Bayesian disease mapping. Biometrical Journal. 59(1), 41-56. doi: 10.1002/bimj.201600018
Nolan, T. H., & Wand M. (2017).  Accurate logistic variational message passing: algebraic and numerical details. Stat. 6(1), 102-112. doi: 10.1002/sta4.139
Johnson, S., Logan M., Fox D., Kirkwood J., Pinto U., & Mengersen KL. (2017).  Environmental decision-making using Bayesian networks: Creating an environmental report card. Applied Stochastic Models in Business and Industry. doi: 10.1002/asmb.2190
Cespedes, M. I., Fripp J., McGree J., Drovandi C. C., Mengersen KL., & Doecke J. D. (2017).  Comparisons of neurodegeneration over time between healthy ageing and Alzheimer's disease cohorts via Bayesian inference. BMJ Open. 7(2), 12174-12174. doi: 10.1136/bmjopen-2016-012174
Mandjes, M., Patch B., & Walton N. (2017).  Detecting Markov Chain Instability: A Monte Carlo Approach. Stochastic Systems.
Vaisman, R., & Kroese D. P. (2017).  Stochastic Enumeration Method for Counting Trees. Methodology and Computing in Applied Probability. 19(1), 31 - 73. doi: 10.1007/s11009-015-9457-4
García-Díaz, P., Ross J. V., Woolnough A. P., & Cassey P. (2017).  The illegal wildlife trade is a likely source of alien species. Conservation Letters. doi: 10.1111/conl.12301
Anderson, C., & Ryan L. M. (2017).  A Comparison of Spatio-Temporal Disease Mapping Approaches Including an Application to Ischaemic Heart Disease in New South Wales, Australia. International Journal of Environmental Research and Public Health. 14(2), 146-162. doi: 10.3390/ijerph14020146
Samuelson, A., Haigh A., O'Reilly MM., & Bean N. G. (2017).  Stochastic model for maintenance in continuously deteriorating systems. European Journal of Operational Research. 259(3), 1169-1179. doi: 10.1016/j.ejor.2016.11.032
Zhu, W., & Fan Y. (2017).  A novel approach for Markov random field with intractable normalizing constant on large lattices. Journal of Computational and Graphical Statistics. 1-1. doi: 10.1080/10618600.2017.1317263
Ebert, A., Wu P., Mengersen K., & Ruggeri F. (2017).  Computationally Efficient Simulation of Queues: The R Package queuecomputer. arXiv.
McGree, J. (2017).  Developments of the total entropy utility function for the dual purpose of model discrimination and parameter estimation in Bayesian design. Computational Statistics & Data Analysis. doi: 10.1016/j.csda.2016.05.020
Friel, N., McKeone J. P., Oates C., & Pettitt A.N. (2017).  Investigation of the widely applicable Bayesian information criterion. Statistics and Computing. doi: 10.1007/s11222-016-9657-y
Vaisman, R., Roughan M., & Kroese D. P. (2017).  The Multilevel Splitting algorithm for graph colouring with application to the Potts model. Philosophical Magazine. 97(19), 1646 - 1673. doi: 10.1080/14786435.2017.1312023
García-Díaz, P., Ross J. V., Woolnough A. P., & Cassey P. (2017).  Managing the risk of wildlife disease introduction: Pathway-level biosecurity for preventing the introduction of alien ranaviruses. Journal of Applied Ecology. 54(1), 234-241. doi: 10.1111/1365-2664.12749
Lee, X. J., Fulford G. R., Pettitt A.N., & Ruggeri F. (2017).  A stochastic model for MRSA transmission within a hospital ward incorporating environmental contamination. Epidemiology and Infection. 145(4), 825-838. doi: 10.1017/S0950268816002880
Benham, T., Duan Q., Kroese D., & Liquet B. (2017).   : Cross-Entropy Package for Optimization . Journal of Statistical Software. 76(8),  doi: 10.18637/jss.v076.i08
Fan, Y., de Micheaux P. Lafaye, Penev S., & Salopek D. (2017).  Multivariate nonparametric test of independence. Journal of Multivariate Analysis. 153, 189-210. doi: 10.1016/j.jmva.2016.09.014
Loertscher, S., Muir E., & Taylor P. (2017).  A general noncentral hypergeometric distribution. Communications in Statistics - Theory and Methods. 4579-4598. doi: 10.1080/03610926.2015.1088033
Price, L.. F., Drovandi C.. C., Lee A.., & Nott D.. J. (2017).  Bayesian Synthetic Likelihood. Journal of Computational and Graphical Statistics. 1 - 11. doi: 10.1080/10618600.2017.1302882
Lawson, B. A. J., & Pettet G. J. (2017).  Space-limited mitosis in the Glazier–Graner–Hogeweg model. Bulletin of Mathematical Biology. 79(1), 1-20. doi: 10.1007/s11538-016-0204-y
Oates, C., Kasza J., Simpson J. A., & Forbes A. B. (2017).  Repair of partly misspecified causal diagrams. Epidemiology.
Duan, Q., & Kroese D. P. (2017).  Splitting for Multi-objective Optimization. Methodology and Computing in Applied Probability. doi: 10.1007/s11009-017-9572-5
Li, J., Nott D.J., Fan Y., & Sisson S. (2017).  Extending approximate Bayesian computation methods to high dimensions via a Gaussian copula model. Computational Statistics & Data Analysis. 106, 77-89. doi: 10.1016/j.csda.2016.07.005
Isaak, D. J., Hoef J. M. Ver, Peterson E., Horan D., & Nagel D. (2017).  Scalable population estimates using spatial-stream-network (SSN) models, fish density surveys, and national geospatial database frameworks for streams. Canadian Journal of Fisheries and Aquatic Sciences. 74(2), 147-156. doi: 10.1139/cjfas-2016-0247
Rodrigues, T., & Fan Y. (2017).  Regression adjustment for noncrossing Bayesian quantile regression. Journal of Computational and Graphical Statistics. doi: 10.1080/10618600.2016.1172016
Psaltis, S. T. P., Farrell T., Burrage K., Burrage P., McCabe P., Moroney T. J., et al. (2017).  Using Population of Models to investigate and quantify gas production in a spatially heterogeneous coal seam gas field. Applied Mathematical Modelling. doi: 10.1016/j.apm.2017.05.005
Peterson, E. E., & Pearse A. R. (2017).  IDW-Plus: An ArcGIS Toolset for Calculating Spatially Explicit Watershed Attributes for Survey Sites. JAWRA Journal of the American Water Resources Association. doi: 10.1111/1752-1688.12558
Thomas, A., Toms L-M. L., Harden F. A., Hobson P., White N., Mengersen KL., et al. (2017).  Concentrations of organochlorine pesticides in pooled human serum by age and gender. Environmental Research. 154, 10-18. doi: 10.1016/j.envres.2016.12.009
Feng, L.B., Zhuang P., Liu F., Turner I., Anh V., & Li J. (2017).  A fast second-order accurate method for a two-sided space-fractional diffusion equation with variable coefficients. Computers & Mathematics with Applications. doi: 10.1016/j.camwa.2016.06.007
Stark, T. L., Liberles D. A., Holland B. R., & O'Reilly MM. (2017).  Analysis of a mechanistic Markov model for gene duplicates evolving under subfunctionalization. BMC Evolutionary Biology. 17, 1-16. doi: 10.1186/s12862-016-0848-0
Tobler, R., Rohrlach AB., Bover P., Llamas B., Tuke J., Bean N. G., et al. (2017).  Aboriginal mitochondrial genetic lineages reveal founding population movements and regionalism in Australia. Nature.
Forrester, P. (2016).  Analogies between random matrix ensembles and the one-component plasma in two-dimensions. Nuclear Physics B. 904, 253-281. doi: 10.1016/j.nuclphysb.2016.01.014
Kang, S. Y., Cramb S., White N., Ball S. J., & Mengersen KL. (2016).  Making the most of spatial information in health: a tutorial in Bayesian disease mapping for areal data. Geospatial Health. 11(2),  doi: 10.4081/gh.2016.428
Duan, Q., & Kroese D. (2016).  Splitting for optimization. Computers & Operations Research. 73, 119-131. doi: 10.1016/j.cor.2016.04.015
Gemmell, P., Burrage K., Rodríguez B. R., & Quinn T. A. (2016).  Rabbit-specific computational modelling of ventricular cell electrophysiology: Using populations of models to explore variability in the response to ischemia. Progress in Biophysics and Molecular Biology. 121(2), 169-184. doi: 10.1016/j.pbiomolbio.2016.06.003
Scharth, M., & Kohn R. (2016).  Particle efficient importance sampling. Journal of Econometrics. 190(1), 133-147. doi: 10.1016/j.jeconom.2015.03.047
Drovandi, C. C., Pettitt A.N., & McCutchan R. A. (2016).  Exact and approximate Bayesian inference for low integer-valued time series models with intractable likelihoods. Bayesian Analysis. 11(2), 325-352. doi: 10.1214/15-BA950
Huque, MH., Bondell H. D., Carroll R. J., & Ryan L. M. (2016).  Spatial regression with covariate measurement error: A semiparametric approach. Biometrics. 72(3), 678-686. doi: 10.1111/biom.12474
Scheinhardt, W. R. W., & Kroese D. P. (2016).  A comparison of random walks in dependent random environmentsAbstract. Advances in Applied Probability. 48(01), 199 - 214. doi: 10.1017/apr.2015.13
Johnston, S. T., Ross J. V., Binder B. J., McElwain D.L. Sean, Haridas P., & Simpson M. J. (2016).  Quantifying the effect of experimental design choices for in vitro scratch assays. Journal of Theoretical Biology. 400, 19-31. doi: 10.1016/j.jtbi.2016.04.012
Mowla, A., Taimre T., Lim Y. L., Bertling K., Wilson S. J., Prow T. W., et al. (2016).  A compact laser imaging system for concurrent reflectance confocal microscopy and laser doppler flowmetry. IEEE Photonics Journal. 8(5), 1-9. doi: 10.1109/JPHOT.2016.2599014
Cramb, S., Mengersen KL., Lambert P. C., Ryan L. M., & Baade P. D. (2016).  A flexible parametric approach to examining spatial variation in relative survival. Statistics in Medicine. 35(29), 5448-5463. doi: 10.1002/sim.7071
Geweke, J. (2016).  Sequentially adaptive Bayesian learning for a nonlinear model of the secular and cyclical behavior of US real GDP. Econometrics. 4(1),  doi: 10.3390/econometrics4010010
Collevecchio, A., Garoni T., Hyndman T., & Tokarev D. (2016).  The worm process for the Ising model is rapidly mixing. Journal of Statistical Physics. 164(5), 1082-1102. doi: 10.1007/s10955-016-1572-2
Stephen, D., & Barnett A. G. (2016).  Effect of temperature and precipitation on salmonellosis cases in South-East Queensland, Australia: an observational study. BMJ Open. 6(2),  doi: 10.1136/bmjopen-2015-010204
Asmussen, S., Jensen J. L., & Rojas-Nandayapa L. (2016).  Exponential family techniques for the lognormal left tail. Scandinavian Journal of Statistics. 43(3), 774-787. doi: 10.1111/sjos.12203
Wells, J. A., Wilson K. A., Abram N. K., Nunn M., Gaveau D. L. A., Runting R. K., et al. (2016).  Rising floodwaters: Mapping impacts and perceptions of flooding in Indonesian Borneo. Environmental Research Letters. 11(6),  doi: 10.1088/1748-9326/11/6/064016
Huque, MH., Anderson C., Walton R., & Ryan L. M. (2016).  Individual level covariate adjusted conditional autoregressive (indiCAR) model for disease mapping. International Journal of Health Geographics. 15(1),  doi: 10.1186/s12942-016-0055-7
Price, D. J., Bean N. G., Ross J. V., & Tuke J. (2016).  On the efficient determination of optimal Bayesian experimental designs using ABC: A case study in optimal observation of epidemics. Journal of Statistical Planning and Inference. 172, 1-15. doi: 10.1016/j.jspi.2015.12.008
Braunsteins, P., Hautphenne S., & Taylor P. (2016).  The roles of coupling and the deviation matrix in determining the value of capacity in M/M/1/C queues. Queueing Systems. 83(1-2), 157-179. doi: 10.1007/s11134-016-9480-3
Y. Y Lee, C., & Wand M. (2016).  Variational methods for fitting complex Bayesian mixed effects models to health data. Statistics in Medicine. 35(2), 165-188. doi: 10.1002/sim.6737
Vaisman, R., Kroese D., & Gertsbakh I. B. (2016).  Improved sampling plans for combinatorial invariants of coherent systems. IEEE Transactions on Reliability. 65(1), 410-424. doi: 10.1109/TR.2015.2446471
Chen, S., Liu F., Jiang X., Turner I., & Burrage K. (2016).  Fast finite difference approximation for identifying parameters in a two-dimensional space-fractional nonlocal model with variable diffusivity coefficients. SIAM Journal on Numerical Analysis. 54(2), 606-624. doi: 10.1137/15M1019301
Olson, R., Fan Y., & Evans J. P. (2016).  A simple method for Bayesian model averaging of regional climate model projections: Application to southeast Australian temperatures. Geophysical Research Letters. 43(14), 7661-7669. doi: 10.1002/2016GL069704
Rodrigues, G. S., Nott D. J., & Sisson S. (2016).  Functional regression approximate Bayesian computation for Gaussian process density estimation. Computational Statistics and Data Analysis. 103, 229-241. doi: 10.1016/j.csda.2016.05.009
Mulhall, B. P., Wright ST., De La Mata N., Allen D., Brown K., Dickson B., et al. (2016).  Risk factors associated with incident sexually transmitted infections in HIV-positive patients in the Australian HIV Observational Database: A prospective cohort study. HIV Medicine. 17(8), 623-630. doi: 10.1111/hiv.12371
Pueyo, E., Dangerfield C. E., Britton O. J., Virág L., Kistamás K., Szentandrássy N., et al. (2016).  Experimentally-based computational investigation into beat-to-beat variability in ventricular repolarization and its response to ionic current inhibition. PLOS ONE. 11(3),  doi: 10.1371/journal.pone.0151461
S. Ghaemi, R., Delalat B., Cetó X., Harding F. J., Tuke J., & Voelcker N. H. (2016).  Synergistic influence of collagen I and BMP 2 drives osteogenic differentiation of mesenchymal stem cells: A cell microarray analysis. Acta Biomaterialia. 34, 41-52. doi: 10.1016/j.actbio.2015.07.027
Ryan, E. G., Drovandi C. C., McGree J., & Pettitt A.N. (2016).  A Review of Modern Computational Algorithms for Bayesian Optimal Design. International Statistical Review. 84(1), 128-154. doi: 10.1111/insr.12107
Anees, A., Aryal J., O'Reilly MM., Gale T. J., & Wardlaw T. (2016).  A robust multi-kernel change detection framework for detecting leaf beetle defoliation using Landsat 7 ETM+ data. ISPRS Journal of Photogrammetry and Remote Sensing. 122, 167-178. doi: 10.1016/j.isprsjprs.2016.10.011
Delaigle, A., & Hall P. (2016).  Methodology for non-parametric deconvolution when the error distribution is unknown. Journal of the Royal Statistical Society: Series B (Statistical Methodology). 78(1), 231-252. doi: 10.1111/rssb.12109
Brown, R., Bruza P., Heard W., Mengersen KL., & Murray J. (2016).  On the (virtual) getting of wisdom: Immersive 3D interfaces for eliciting spatial information from experts. Spatial Statistics. 18(Part A), 318-331. doi: 10.1016/j.spasta.2016.07.001
Oates, C., Papamarkou T., & Girolami M. (2016).  The controlled thermodynamic integral for Bayesian model evidence evaluation. Journal of the American Statistical Association. 111(514), 634-645. doi: 10.1080/01621459.2015.1021006
Ballard, P. G., Bean N. G., & Ross J. V. (2016).  The probability of epidemic fade-out is non-monotonic in transmission rate for the Markovian SIR model with demography. Journal of Theoretical Biology. 393, 170-178. doi: 10.1016/j.jtbi.2016.01.012
Buchmann, B., Fan Y., & Maller R. A. (2016).  Distributional representations and dominance of a Lévy process over its maximal jump processes. Bernoulli. 22(4), 2325-2371. doi: 10.3150/15-BEJ731
Qin, S., Liu F., Turner I., Yu Q., Yang Q., & Vegh V. (2016).   Characterization of anomalous relaxation using the time-fractional Bloch equation and multiple echo T *-weighted magnetic resonance imaging at 7 T . Magnetic Resonance in Medicine. doi: 10.1002/mrm.26222
Hsieh, J. C., Cramb S., McGree J., Dunn N. A. M., Baade P. D., & Mengersen KL. (2016).  Spatially varying coefficient inequalities: Evaluating how the impact of patient characteristics on breast cancer survival varies by location. PLOS ONE. 11(5),  doi: 10.1371/journal.pone.0155086
Wijesiri, B., Egodawatta P., McGree J., & Goonetilleke A. (2016).  Understanding the uncertainty associated with particle-bound pollutant build-up and wash-off: A critical review. Water Research. 101, 582-596. doi: 10.1016/j.watres.2016.06.013
Zhao, Y., Zhang Y., Liu F., Turner I., Tang Y., & Anh V. (2016).  Convergence and superconvergence of a fully-discrete scheme for multi-term time fractional diffusion equations. Computers & Mathematics with Applications. doi: 10.1016/j.camwa.2016.05.005
Doosti, H., & Hall P. (2016).  Making a non-parametric density estimator more attractive, and more accurate, by data perturbation. Journal of the Royal Statistical Society: Series B (Statistical Methodology). 78(2), 445-462. doi: 10.1111/rssb.12120
Delorme, P., P. de Micheaux L., Liquet B., & Riou J. (2016).  Type-II generalized family-wise error rate formulas with application to sample size determination. Statistics in Medicine. 35(16), 2687-2714. doi: 10.1002/sim.6909
Guttmann, A., Jensen I., Maillard J. M., & Pantone J. (2016).  Is the full susceptibility of the square-lattice Ising model a differentially algebraic function?. Journal of Physics A: Mathematical and Theoretical. 49(50),  doi: 10.1088/1751-8113/49/50/504002
Beaudequin, D., Harden F., Roiko A., & Mengersen KL. (2016).  Utility of Bayesian networks in QMRA-based evaluation of risk reduction options for recycled water. Science of The Total Environment. 541, 1393-1409. doi: 10.1016/j.scitotenv.2015.10.030
Forrester, P., & Liu D. (2016).  Singular values for products of complex Ginibre matrices with a source: Hard edge limit and phase transition. Communications in Mathematical Physics. 344(1), 333-368. doi: 10.1007/s00220-015-2507-5
Huang, X., Clements A., Williams G., Mengersen KL., Tong S., & Hu W. (2016).  Bayesian estimation of the dynamics of pandemic (H1N1) 2009 influenza transmission in Queensland: A space–time SIR-based model. Environmental Research. 146, 308-314. doi: 10.1016/j.envres.2016.01.013
Reddan, T., Corness J., Powell J., Harden F., & Mengersen KL. (2016).  Stumped? It could be stump appendicitis. Sonography. doi: 10.1002/sono.12098
Tran, M., Nott D., Kuk A., & Kohn R. (2016).  Parallel variational Bayes for large datasets with an application to generalized linear mixed models. Journal of Computational and Graphical Statistics. 25(2), 626-646. doi: 10.1080/10618600.2015.1012293
McGrory, C.A., Pettitt A.N., Titterington D.M., Alston C.L., & Kelly M. (2016).  Transdimensional sequential Monte Carlo using variational Bayes — SMCVB. Computational Statistics & Data Analysis. 93, 246-254. doi: 10.1016/j.csda.2015.03.006
Hargrave, C., Mason N., Guidi R., Miller J-A., Becker J., Moores M., et al. (2016).   Automated replication of cone beam CT-guided treatments in the Pinnacle treatment planning system for adaptive radiotherapy . Journal of Medical Radiation Sciences. 63(1), 48-58. doi: 10.1002/jmrs.141
Vaisman, R., Kroese D. P., & Gertsbakh I. B. (2016).  Splitting sequential Monte Carlo for efficient unreliability estimation of highly reliable networks. Structural Safety. 63, 1 - 10. doi: 10.1016/j.strusafe.2016.07.001
Heinrich, S., Wittmann T. A., Prowse T. A. A., Ross J. V., Delean S., Shepherd C. R., et al. (2016).  Where did all the pangolins go? International CITES trade in pangolin species. Global Ecology and Conservation. 8, 241-253. doi: 10.1016/j.gecco.2016.09.007
Kenway, S. J., Binks A., Scheidegger R., Bader H.P., Pamminger F., Lant P., et al. (2016).  Household analysis identifies water-related energy efficiency opportunities. Energy and Buildings. 131, 21-34. doi: 10.1016/j.enbuild.2016.09.008
Waller, D., Mondy P., Brama T., Fisher J., King A., Malkov K., et al. (2016).  Determining the effect of vein visualization technology on donation success, vasovagal symptoms, anxiety and intention to re-donate in whole blood donors aged 18-30 years: A randomized controlled trial. Vox Sanguinis. 111(2), 135-143. doi: 10.1111/vox.12407
Geweke, J. (2016).  Comment on: Reflections on the probability space induced by moment conditions with implications for Bayesian inference. Journal of Financial Econometrics. 14(2), 253-257. doi: 10.1093/jjfinec/nbv011
de Gier, J., Feher G. Z., Nienhuis B., & Rusaczonek M. (2016).  Integrable supersymmetric chain without particle conservation. Journal of Statistical Mechanics: Theory and Experiment. 2016(2),  doi: 10.1088/1742-5468/2016/02/023104
Kiley, D. P., Reagan A. J., Mitchell L., Danforth C. M., & Dodds P. S. (2016).  Game story space of professional sports: Australian rules football. Physical Review E. 93(5),  doi: 10.1103/PhysRevE.93.052314
Tuyl, F., Gerlach R., & Mengersen KL. (2016).  Consensus priors for multinomial and binomial ratios. Journal of Statistical Theory and Practice. 10(4), 736-754. doi: 10.1080/15598608.2016.1219684
Dini, S., Binder B. J., Fischer S. C., Mattheyer C., Schmitz A., Stelzer E. H. K., et al. (2016).  Identifying the necrotic zone boundary in tumour spheroids with pair-correlation functions. Journal of The Royal Society Interface. 13(123),  doi: 10.1098/rsif.2016.0649
Maillardet, R. J., & Taylor P. (2016).  Queues with advanced reservations: An infinite-server proxy for the bookings diary. Advances in Applied Probability. 48(01), 13-31. doi: 10.1017/apr.2015.4
Kim, A. S. I., & Wand M. (2016).  The explicit form of expectation propagation for a simple statistical model. Electronic Journal of Statistics. 10(1), 550-581. doi: 10.1214/16-EJS1114
Duan, Q., & Kroese D. P. (2016).  Splitting for optimization. Computers & Operations Research. 73, 119 - 131. doi: 10.1016/j.cor.2016.04.015
Turschwell, M. P., Peterson E., Balcombe S. R., & Sheldon F. (2016).  To aggregate or not? Capturing the spatio-temporal complexity of the thermal regime. Ecological Indicators. 67, 39-48. doi: 10.1016/j.ecolind.2016.02.014
Spettl, A., Brereton T., Duan Q., Werz T., Krill C. E., Kroese D., et al. (2016).  Fitting Laguerre tessellation approximations to tomographic image data. Philosophical Magazine. 96(2), 166-189. doi: 10.1080/14786435.2015.1125540
McVinish, R., Pollett P., & Shausan A. (2016).  Limiting the spread of disease through altered migration patterns. Journal of Theoretical Biology. 393, 60-66. doi: 10.1016/j.jtbi.2015.12.019
Schiffner, I., Perez T., Srinivasan M. V., & Osorio D. (2016).  Strategies for pre-emptive mid-air collision avoidance in budgerigars. PLOS ONE. 11(9),  doi: 10.1371/journal.pone.0162435
Lorenz, R., Pitman A. J., & Sisson S. (2016).  Does Amazonian deforestation cause global effects; can we be sure?. Journal of Geophysical Research: Atmospheres. 121(10), 5567-5584. doi: 10.1002/2015JD024357
Walton, D. C., Hiho S. J., Cantwell L. S., Diviney M. B., Wright ST., Snell G. I., et al. (2016).  HLA matching at the eplet level protects against chronic lung allograft dysfunction. American Journal of Transplantation. 16(9), 2695-2703. doi: 10.1111/ajt.13798
Niu, Y., Burrage K., & Chen L. (2016).  Modelling biochemical reaction systems by stochastic differential equations with reflection. Journal of Theoretical Biology. 396, 90-104. doi: 10.1016/j.jtbi.2016.02.010
Delacroix, S., Chokka R., Nelson A., Sidharta S., Teo K., Tuke J., et al. (2016).  Safety and efficacy of pro ANP 31-67 in cardiorenal syndrome: A first-in-human trial. Journal of the American College of Cardiology. 67(13),  doi: 10.1016/S0735-1097(16)31352-3
Anees, A., Aryal J., O'Reilly MM., & Gale T. J. (2016).  A relative density ratio-based framework for detection of land cover changes in MODIS NDVI time series. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. 9(8), 3359-3371. doi: 10.1109/JSTARS.2015.2428306
Peköz, E. A., Röllin A., & Ross N. (2016).  Generalized gamma approximation with rates for urns, walks and trees. The Annals of Probability. 44(3), 1776-1816. doi: 10.1214/15-AOP1010
Oates, C., Smith J. Q., & Mukherjee S. (2016).  Estimating causal structure using conditional DAG models. Journal of Machine Learning Research. 17(54), 1-23.
Bean, N. G., Eshragh A., & Ross J. V. (2016).  Fisher Information for a partially observable simple birth process. Communications in Statistics - Theory and Methods. 45(24), 7161-7183. doi: 10.1080/03610926.2014.978024
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Chakraborty, S., Mengersen KL., Fidge C., Ma L., Lassen D., & Shi Y. (2015).  Multifaceted Modelling of Complex Business Enterprises. PLOS ONE. 10(8),  doi: 10.1371/journal.pone.0134052
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Davis, S., Abbasi B., Shah S., Telfer S., & Begon M. (2014).  Spatial analyses of wildlife contact networks. Journal of The Royal Society Interface. 12(102), 20141004-20141004. doi: 10.1098/rsif.2014.1004
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