Found 1240 results
Kennedy, DW., White N., Mengersen KL., & Lea R. (Submitted).  Cell-type specific analysis of heterogeneous methylation signal using a Bayesian model-based approach.
In Press
Chong, H. Phern, J. Frøen F., Richardson S., Liquet B.., D. Charnock-Jones S., & Smith G. C. S. (In Press).  Age at menarche and the risk of operative delivery. The Journal of Maternal-Fetal & Neonatal Medicine. 1 - 8.
Price, L.. F., Drovandi C. C., Lee A.., & Nott D.. J. (In Press).  Bayesian Synthetic Likelihood. Journal of Computational and Graphical Statistics. 1 - 11.
Feng, L.B., Zhuang P., Liu F., Turner I., & Li J. (In Press).  High-order numerical methods for the Riesz space fractional advection–dispersion equations. Computers & Mathematics with Applications.
Wu, P., McMahon K., Rasheed M. A., Kendrick G. A., York P. H., Chartrand K., et al. (In Press).  Managing seagrass resilience under cumulative dredging affecting light: Predicting risk using dynamic Bayesian networks. Journal of Applied Ecology.
Olson, R.., An S.-I.., Fan Y.., Evans J.. P., & Caesar L.. (In Press).  North Atlantic observations sharpen meridional overturning projections. Climate Dynamics.
Abdullah, FA., Liu F., Burrage P., Burrage K., & Li T. (In Press).  Novel analytical and numerical techniques for fractional temporal SEIR measles model. Numerical Algorithms. 1–22.
Zhu, W., & Fan Y. (In Press).  A novel approach for Markov random field with intractable normalizing constant on large lattices. Journal of Computational and Graphical Statistics. 1-1.
Cope, R. C., Ross J. V., Wittmann T. A., Watts M. J., & Cassey P. (In Press).  Predicting the Risk of Biological Invasions Using Environmental Similarity and Transport Network Connectedness. Risk Analysis.
Turschwell, M. P., Stewart-Koster B., Leigh C., Peterson E., Sheldon F., & Balcombe S.R.. (In Press).  Riparian restoration offsets predicted population consequences of climate warming in a threatened headwater fish. Aquatic Conservation.
Quiroz, M., Tran M-N., Villani M., & Kohn R. (In Press).  Speeding up MCMC by delayed acceptance and data subsampling. Journal of Computational and Graphical Statistics.
Quiroz, M., Tran M-N., Villani M., & Kohn R. (In Press).  Speeding up MCMC by delayed acceptance and data subsampling. Journal of Computational and Graphical Statistics.
Quiroz, M., Kohn R., Villani M., & Tran M-N. (In Press).  Speeding up MCMC by efficient data subsampling. Journal of American Statistical Association.
Duan, Q., & Kroese D. (In Press).  Splitting for Multi-objective Optimization. Methodology and Computing in Applied Probability.
Shah, R., & Kroese D. (In Press).  Without-replacement sampling for particle methods on finite state spaces. Statistics and Computing.
Fan, Y.., Meikle S.. R., Angelis G.., & Sitek A.. (2018).  ABC in nuclear imaging. Handbook of Approximate Bayesian Computation.
Overstall, A. M., McGree J., & Drovandi C. C. (2018).  An approach for finding fully Bayesian optimal designs using normal-based approximations to loss functions. Statistics and Computing.
Peralta, O., Rojas-Nandayapa L., Xie W., & Yao H. (2018).  Approximation of ruin probabilities via Erlangized scale mixtures. Insurance: Mathematics and Economics.
Gunawan, D., Griffiths W. E., & Chotikapanich D. (2018).  Bayesian inference for health inequality and welfare using qualitative data. Economics Letters. 162, 76 - 80.
Fan, X., Li B., & Sisson S. (2018).  The Binary Space Partitioning-Tree Process. The 21st International Conference on Artificial Intelligence and Statistics (AISTATS 2018).
Bedini, A.., Zhang L., & Garoni T. (2018).  A Case Study of a Continuous Flow Intersection and Its Impact on Public Transport. IEEE ITSC.
Jahan, F. (2018).  Comparison of Missing value Estimation Techniques in Rainfall Data of Bangladesh. Theoretical and Applied Climatology.
Collevecchio, A., Elçi E. Metin, Garoni T. M., & Weigel M. (2018).  On the Coupling Time of the Heat-Bath Process for the Fortuin–Kasteleyn Random–Cluster Model. Journal of Statistical Physics.
Wu, P., M. Caley J., Kendrick G. A., McMahon K., & Mengersen KL. (2018).  Dynamic Bayesian network inferencing for non-homogeneous complex systems. Journal of the Royal Statistical Society: Series C (Applied Statistics).
Andersen, L. Nørvang, Laub P., & Rojas-Nandayapa L. (2018).  Efficient Simulation for Dependent Rare Events with Applications to Extremes. Methodology and Computing in Applied Probability.
Donovan, D., Burrage K., Burrage P., McCourt TA., Thompson B., & Yazici EŞ. (2018).  Estimates of the coverage of parameter space by Latin Hypercube and Orthogonal Array-based sampling. Applied Mathematical Modelling.
Rebuli, N. P., Bean N. G., & Ross J.V.. (2018).  Estimating the basic reproductive number during the early stages of an emerging epidemic. Theoretical Population Biology.
Kuhn, J., Mandjes M., & Taimre T. (2018).  EXACT ASYMPTOTICS OF SAMPLE-MEAN-RELATED RARE-EVENT PROBABILITIES. Probability in the Engineering and Informational Sciences. 1 - 22.
L Nandayapa, R., & Bladt M. (2018).  Fitting phase–type scale mixtures to heavy–tailed data and distributions. Extremes.
Quiroz, M., Nott D. J., & Kohn R. (2018).  Gaussian variational approximations for high-dimensional state space models.
Nott, D. J., Ong V.. M. - H., Fan Y.., & Sisson S. A. (2018).  High dimensional ABC. Handbook of Approximate Bayesian Computation.
Lee, J. Y. L., & Ryan L. M. (2018).  Identifying Faltering in Longitudinal Child Growth Studies. International Biometric Conference.
Drovandi, C. C., & Tran M-N. (2018).  Improving the Efficiency of Fully Bayesian Optimal Design of Experiments Using Randomised Quasi-Monte Carlo. Bayesian Analysis. 13(1), 139 - 162.
Muñoz, M. A., Villanova L., Baatar D., & Smith-Miles K. (2018).  Instance spaces for machine learning classification. Machine Learning. 107(1), 109 - 147.
Coutts, S. R., Helmstedt K. J., & Bennett J. R. (2018).  Invasion lags: The stories we tell ourselves and our inability to infer process from pattern. (Roura-Pascual, N., Ed.).Diversity and Distributions.
Fiems, D., Mandjes M., & Patch B. (2018).  Networks of infinite-server queues with multiplicative transitions. Performance Evaluation.
Bergmeir, C., Hyndman R. J., & Koo B. (2018).  A note on the validity of cross-validation for evaluating autoregressive time series prediction. Computational Statistics & Data Analysis. 120, 70-83.
Ye, N., Roosta-Khorasani F., & Cui T. (2018).  Optimization Methods for Inverse Problems. Computational Inverse Problems.
Meier, A.D.., de Laat M.A.., Reiche D.B.., Pollitt C.C.., Walsh D.M.., McGree J., et al. (2018).  The oral glucose test predicts laminitis risk in ponies fed a diet high in nonstructural carbohydrates. Domestic Animal Endocrinology. 63, 1 - 9.
Sisson, S. A., Fan Y.., & beaumont M.. A. (2018).  Overview of Approximate Bayesian computation. Handbook of Approximate Bayesian Computation.
Saviniec, L.., Santos M.O.., & Costa A.M.. (2018).  Parallel local search algorithms for high school timetabling problems. European Journal of Operational Research. 265,
Whyte, J. M. (2018).  The practical value of an explicit response model in quantitative uses of Biacore™ biosensors. bioRxiv.
Gertsbakh, I. B., Shpungin Y., & Vaisman R. (2018).  Reliability of a Network with Heterogeneous Components. (Lisnianski, A., Frenkel I., & Karagrigoriou A., Ed.).Recent Advances in Multi-state Systems Reliability. 3 - 18.
Hoef, J. M. Ver, Peterson E., Hooten M. B., Hanks E. M., & Fortin M-J. (2018).  Spatial Autoregressive Models for Statistical Inference from Ecological Data. Ecological Monographs.
Whyte, J. M. (2018).  Tend to your model or data may pull the wool over your eyes. Mathematics of Biological Systems Modelling Symposium, April 2018, Melbourne.
Patch, B., & Taimre T. (2018).  Transient provisioning and performance evaluation for cloud computing platforms: A capacity value approach. Performance Evaluation. 118,
Lawson, B. A. J., Drovandi C. C., Cusimano N., Burrage P., Rodriguez B., & Burrage K. (2018).  Unlocking data sets by calibrating populations of models to data density: A study in atrial electrophysiology. Science Advances. 4(1), e1701676.
Wijesiri, B., Deilami K., McGree J., & Goonetilleke A. (2018).  Use of surrogate indicators for the evaluation of potential health risks due to poor urban water quality: A Bayesian Network approach. Environmental Pollution. 233, 655 - 661.
Vercelloni, J.., Clifford S.., Caley M.J.., Pearse A.R.., Brown R.., James A.., et al. (2018).  Using virtual reality to estimate aesthetic values of coral reefs. Royal Society Open Science.
Vercelloni, J., Clifford S., M. Caley J., Pearse A. R., Brown R., James A., et al. (2018).  Using virtual reality to estimate aesthetic values of coral reefs. Royal Society Open Science. 5(4), 172226.
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