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2019
Liu, Z.., Liu F.., & Zeng F. (2019).  An alternating direction implicit spectral method for solving two dimensional multi-term time fractional mixed diffusion and diffusion-wave equations. Applied Numerical Mathematics. 136, 139 - 151.
Wu, P. Pao‐Yen, Mengersen KL., M. Caley J., McMahon K., Rasheed M. A., Kendrick G. A., et al. (2019).  Analysing the dynamics and relative influence of variables affecting ecosystem responses using functional PCA and boosted regression trees: A seagrass case study. Methods in Ecology and Evolution. 10(10), 1723 - 1733.
Hyndman, R. J. (2019).  Analysis of 2018 ITI Data.
Zhang, J.., Liu F.., Lin Z.., & Anh V. (2019).  Analytical and numerical andsolutions for a multi-term time fractional Burger's fluid model. Applied Mathematics and Computation. 356, 1-12.
Zhang, J.., Liu F.., & Anh V. (2019).  Analytical and numerical solutions for a two dimensional time fractional Oldroyd-B model. Numerical Methods for Partial Differential Equations. 35(3), 875-893.
Eshragh, A., Esmaeilbeigi R., & Middleton R. (2019).  An Analytical Bound on the Fleet Size in Vehicle Routing Problems: A Dynamic Programming Approach.
Shen, S.., Liu F.., & Anh V. (2019).  The analytical solution and numerical solutions for a two-dimensional multi-term time fractional diffusion and diffusion-wave equation. Journal of Computational and Applied Mathematics. 345, 515-534.
Bilal, A., Rextin A., Kakakhel A., & Nasim M. (2019).  Analyzing Emergent Users’ Text Messages Data and Exploring Its Benefits. IEEE Access. 7, 2870 - 2879.
Capdevila, B., Laa U., & Valencia G. (2019).  Anatomy of a six-parameter fit to the b-> sl+l- anomalies. The European Physical Journal C. 79(6), 462.
Liu, C., Zheng L., Lin P., Pan M., & Liu F. (2019).  Anomalous diffusion in rotating Casson fluid through a porous medium. Physica A: Statistical Mechanics and its Applications. 528, 121431.
Talagala, P. Dilini, Hyndman R. J., & Smith-Miles K. (2019).  Anomaly Detection in High Dimensional Data. arXiv. arXiv:1908.04000v1.
Talagala, P. Dilini (2019).  Anomaly Detection in R. useR! 2019.
Suhr, E. L., O'Dowd D. J., Suarez A. V., Cassey P., Wittmann T. A., Ross J. V., et al. (2019).  Ant interceptions reveal roles of transport and commodity in identifying biosecurity risk pathways into Australia. NeoBiota. 53, 1 - 24.
Thomas, A., White N. M., Toms L-M. Leontjew, & Mengersen KL. (2019).  Application of ensemble methods to analyse the decline of organochlorine pesticides in relation to the interactions between age, gender and time. (Garrett, T. J., Ed.).PLOS ONE. 14(11), e0223956.
Mengersen, KL., Duncan E., Arbel J., Alston-Knox C., & White N. (2019).  Applications in Industry. (Fruhwirth-Schnatter, S., Celeux G., & Robert C. P., Ed.).Handbook of Mixture Analysis.
ISERLES, A.., & MACNAMARA S.. (2019).  Applications of Magnus expansions and pseudospectra to Markov processes. European Journal of Applied Mathematics. 30(2), 400-425.
Frazier, D. T., Maneesoonthorn W., Martin G. M., & McCabe B. P. M. (2019).  Approximate Bayesian forecasting. International Journal of Forecasting. 35(2), 521 - 539.
Fan, Y. (2019).  Approximate Bayesian Inference for Potts models. The 3rd International Conference on Econometrics and Statistics (EcoSta 2019).
Rajapaksha, S., Garoni T. M., & Zhang D.. Joyce (2019).  Approximating Link Travel Time Distributions. 63rd Annual Meeting of the Australian Mathematical Society.
Reinert, G., & Ross N. (2019).  Approximating stationary distributions of fast mixing Glauber dynamics, with applications to exponential random graphs. The Annals of Applied Probability. 29(5), 3201 - 3229.
Leigh, C., Boersma K. S., Galatowitsch M. L., Milner V. S., & Stubbington R. (2019).  Are all rivers equal? The role of education in attitudes towards temporary and perennial rivers. (Gibbs, L., Ed.).People and Nature. 1(2), 181-190.
Tierney, N., Cook D., & McBain M. (2019).  Are we tere yet? Testing the effectiveness of graphics as MCMC diagnostics. John Hopkins University Seminar.
Kou, K., Baade P. David, Guo X., Gatton M., Cramb S., Lu Z., et al. (2019).  Area socioeconomic status is independently associated with esophageal cancer mortality in Shandong, China. Scientific Reports. 9(1), 6388.
Jahan, F., Duncan E., Cramb S., Mengersen KL., & Baade P. (2019).  Augmeting Disease Maps: a Bayesian meta-analysis approach. Young Statisticians Conference 2019.
Kobakian, S. (2019).  An Australian alternative to choropleth maps; visualising geo-spatial disease data. WOMBAT19.
Cramb, S. (2019).  The Australian Cancer Atlas. Locate19.
Duncan, E. (2019).  The Australian Cancer Atlas: mapping reliable small-area estimates of cancer incidence and survival. GEOMED 2019.
Martin, G. M., McCabe B. P. M., Frazier D. T., Maneesoonthorn W., & Robert C. P. (2019).  Auxiliary Likelihood-Based Approximate Bayesian Computation in State Space Models. Journal of Computational and Graphical Statistics. 28(3), 508-522.
Jahan, F., & Mengersen KL. (2019).  Bayesian Empirical Likelihood Spatial Model applying Leroux Structure. Bayes on the Beach 2019.
Jahan, F., & Mengersen KL. (2019).  Bayesian Empirical Likelihood Spatial Model applying Leroux Structure. Young Statisticians Conference 2019.
Moores, M. T., Nicholls G. K., Pettitt A. N., & Mengersen KL. (2019).  Bayesian Indirect Likelihood for the Potts Model. The 12th International Conference on Monte Carlo Methods and Applications.
Tan, B. Kheng, Panagiotelis A., & Athanasopoulos G. (2019).  Bayesian Inference for the One-Factor Copula Model. Journal of Computational and Graphical Statistics. 28(1), 155-173.
Frazier, D. T., Nott D. J., Drovandi C., & Kohn R. (2019).  Bayesian inference using synthetic likelihood: asymptotics and adjustments. arXiv. arXiv:1902.04827v2.
Mengersen, KL. (2019).  Bayesian Learning for Decision Making in the Big Data Era. Bayes on the Beach 2019.
Ullah, I., & Mengersen KL. (2019).  Bayesian mixture models and their Big Data implementations with application to invasive species presence-only data. Journal of Big Data. 6(1), 29.
Walker, J. N., Black A. J., & Ross J. V. (2019).  Bayesian model discrimination for partially-observed epidemic models. Mathematical Biosciences. 317, 108266.
Botha, I., Kohn R., & Drovandi C. (2019).  Bayesian Parameter Inference for Stochastic Differential Equation Mixed Effects Models. The 12th International Conference on Monte Carlo Methods and Applications.
Vo, B. N., Drovandi C. C., & Pettitt A. N. (2019).  Bayesian Parametric Bootstrap for Models with Intractable Likelihoods. Bayesian Analysis. 14(1), 211 - 234.
[Anonymous] (2019).  Bayesian Semiparametric Extremal quantile estimation for Climate projection. WOMBAT Monash Business School.
[Anonymous] (2019).  Bayesian Semiparametric Extremal quantile estimation for Climate projection. MATRIX 2019 .
Aswi, A.., Cramb S., Moraga P., & Mengersen KL. (2019).  Bayesian spatial and spatio-temporal approaches to modelling dengue fever: a systematic review. Epidemiology & Infection. 147, e33.
Aswi, A.., Cramb S., Hu W., White G., & Mengersen KL. (2019).  Bayesian spatio-temporal conditional autoregressive localised model. ACEMS Retreat 2019.
Mengersen, KL. (2019).  Bayesian Statistical Analysis of Large Images. Data Science Down Under 2019.
Santos-Fernández, E., Wu P., & Mengersen KL. (2019).  Bayesian statistics meets sports: a comprehensive review. Journal of Quantitative Analysis in Sports. 15(4), 289 - 312.
Liquet, B. (2019).  Bayesian variable selection regression for group data: application to leverage pleiotropic effect.. International Workshop on Perspectives On High-dimensional Data Analysis.
Shao, Q-M., & Zhang Z. (2019).  Berry-Esseen bound of normal and Nonnormal approximation for unbounded exchangeable pairs. Annals of Probability. 47(1), 61-108.
Corry, P., & Bierwirth C. (2019).  The Berth Allocation Problem with Channel Restrictions. Transportation Science. 53(3), 708-727.
Holloway, J. (2019).  Beta distributions and random forest for better forest monitoring. Bayes on the Beach 2019.
Eshragh, A., Roosta F., Nazari A., & Mahoney M. (2019).  Big Time Series Data and Randomized Numerical Linear Algebra. The 20th INFORMS Applied Probability Society Conference.
Fan, X., Li B., & Sisson S. (2019).  Binary Space Partitioning Forest. (Chaudhuri, K., & Sugiyama M., Ed.).The 22nd International Conference on Artificial Intelligence and Statistics (AISTATS) 2019. 89, 3022-3031.

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