Found 1270 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.
Moka, S.. B., Juneja S.., & Mandjes M.. R. H. (2018).  Analysis of Perfect Sampling Methods for Hard-sphere Models. ACM SIGMETRICS Performance Evaluation Review. 45(2), 69 - 75.
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.
de Gier, J. (2018).  AustMS Early Career Workshop.
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).
.Turner, I.,.Xie H.,.Pearcy M.,.Grote R., &.Colditz P. (2018).  Can Three-Dimensional Mioton Analysis and Fuzzy entropy detect movement differences in General Movement Assessment Categories in the normative infant population?. World Congress of Biomechanics.
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., Sinha N. Chandra, Rahman M.. Mahfuzur, Rahman M.. Morshadur, Mondal M.. Sanaul Haq, & M. Islam A. (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.
Shao, Q-M., & Zhang Z. (2018).  Cramer-type moderate deviations for unbounded exchangeable pairs.
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.
Huggins, R., Stoklosa J., Roach C., & Yip P. (2018).  Estimating the size of an open population using sparse capture–recapture data. Biometrics. 74, 280–288.
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.
Leigh, C., Aspin T. W. H., Matthews T. J., Rolls R. J., & Ledger M. E. (2018).  Extreme drought alters the temporal beta diversity and functional stability of stream invertebrate communities. Australian Freshwater Sciences Society Conference 2018.
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.
Pearse, A. R., Hamilton R. J., Choat J. Howard, Pita J., Almany G., Peterson N., et al. (2018).  Giant coral reef fishes display markedly different susceptibility to night spearfishing. Ecology and Evolution.
Chattopadhyay, A., Blaszczyszyn B., & Keeler P. (2018).  Gibbsian On-Line Distributed Content Caching Strategy for Cellular Networks. IEEE Transactions on Wireless Communications. 17(2), 969 - 981.
Whyte, J. M. (2018).  GLOBAL A PRIORI IDENTIFIABILITY OF MODELS OF FLOW-CELL OPTICAL BIOSENSOR EXPERIMENTS. Bulletin of the Australian Mathematical Society. 98(02), 350 - 352.
Datry, T.., Foulquier A.., Corti R.., von Schiller D.., Tockner K.., Mendoza-Lera C.., et al. (2018).  A global analysis of terrestrial plant litter dynamics in non-perennial waterways. Nature Geoscience. 11(7), 497 - 503.
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.
Hirsch, C., Jahnel B., Keeler P., & Patterson R. (2018).  Large deviations in relay-augmented wireless networks. Queueing Systems. 88(3-4), 349 - 387.
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.
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