Books

Book - edited

1. de Gier, J., Praeger, C. E., Wood, D. R., & Tao, T. (Eds.) (2021). 2019-20 MATRIX Annals. MATRIX Book Series (Vol 4). Cham: Springer. Read online

Book Chapters

Book chapter

1. Whyte, J. M. (2021). Model Structures and Structural Identifiability: What? Why? How? In de Gier, J., Praeger, C. E., Wood, D. R., & Tao, T. (Eds.) (2021). 2019-20 MATRIX Annals. MATRIX Book Series (Vol. 4, pp. 185–213). Cham: Springer. Read online
2. Whyte, J. M. (2021). Branching out into Structural Identifiability Analysis with Maple: Interactive Exploration of Uncontrolled Linear Time-Invariant Structures. In Corless, R.M., Gerhard, J., & Kotsireas, I.S. (Eds.) Maple in Mathematics Education and Research. MC 2020. Communications in Computer and Information Science (Vol. 1414, pp 410-428). Cham: Springer. Read online

Journal Articles

Article in scholarly refereed journal

1. Amiet, B., Collevecchio, A., & Hamza, K. (2021). When “Better” is better than “Best” Operations Research Letters, 49(2), 260 - 264. Read online
2. Amiet, B., Collevecchio, A., Scarsini, M., & Zhong, Z. (2021). Pure Nash Equilibria and Best-Response Dynamics in Random Games. Mathematics Of Operations Research, 46(4), 1552-1572. Read online
3. An, X., Liu, F., Zheng, M., Anh, V. V., & Turner, I. W. (2021). A space-time spectral method for time-fractional Black-Scholes equation. Applied Numerical Mathematics, 165, 152-166. Read online
4. Asanjarani, A., Nazarathy, Y., & Taylor, P. (2021). A survey of parameter and state estimation in queues. Queueing Systems, 97, 39-80. Read online
5. Aswi, A., Cramb, S., Duncan, E., & Mengersen, K. (2021). Detecting Spatial Autocorrelation for a Small Number of Areas: a practical example. Journal Of Physics: Conference Series, 1899(1), 012098. Read online
6. Aswi, A., Sukarna, Cramb, S., & Mengersen, K. (2021). Effects of Climatic Factors on Dengue Incidence: A Comparison of Bayesian Spatio-Temporal Models. Journal Of Physics: Conference Series, 1863(1), 012050. Read online
7. Baghfalaki, T., Sugier, P., Truong, T., Pettitt, A., Mengersen, K., & Liquet, B. (2021). Analyse de la pléiotropie dans les GWAS à l’aide de méthodes bayésiennes prenant en compte la structure de groupe de variables. Revue D'épidémiologie Et De Santé Publique, 69(Supplement 1), S24 - S25. Read online
8. Baghfalaki, T., Sugier, P‐E., Truong, T., Pettitt, A. N., Mengersen, K., & Liquet, B. (2021). Bayesian meta‐analysis models for cross cancer genomic investigation of pleiotropic effects using group structure. Statistics In Medicine, 40(6), 1498-1518. Read online
9. Bardsley, J. M., & Cui, T. (2021). Optimization-Based Markov Chain Monte Carlo Methods for Nonlinear Hierarchical Statistical Inverse Problems. SIAM/ASA Journal On Uncertainty Quantification, 9(1), 29-64. Read online
10. Bean, N. G., O’Reilly, M. M., & Palmowski, Z. (2021). Yaglom limit for stochastic fluid models. Advances In Applied Probability, 53(3), 649 - 686. Read online
11. Ben Taieb, S., Taylor, J. W., & Hyndman, R. J. (2021). Hierarchical Probabilistic Forecasting of Electricity Demand With Smart Meter Data. Journal of the American Statistical Association, 116(533), 27-43. Read online
12. Beranger, B., Padoan, S. A., & Sisson, S. (2021). Estimation and uncertainty quantification for extreme quantile regions. Extremes, 24, 349-375. Read online
13. Bian, L., Cui, T., Yeo, B. T. Thomas, Fornito, A., Razi, A., & Keith, J. (2021). Identification of community structure-based brain states and transitions using functional MRI. NeuroImage, 244, 118635. Read online
14. Bon, J. J., Lee, A., & Drovandi, C. (2021). Accelerating sequential Monte Carlo with surrogate likelihoods. Statistics and Computing, 31, 62. Read online
15. Botha, I., Kohn, R., & Drovandi, C. (2021). Particle Methods for Stochastic Differential Equation Mixed Effects Models. Bayesian Analysis, 16(2), 575-609. Read online
16. Boyle, L. M., Mackay, M., Bean, N., & Roughan, M. (2021). Impact of the COVID-19 pandemic on South Australia. Australian Health Review, 45(5), 533-539. Read online
17. Browning, A. P., Maclaren, O. J., Buenzli, P. R., Lanaro, M., Allenby, M. C., Woodruff, M. A., & Simpson, M. J. (2021). Model-based data analysis of tissue growth in thin 3D printed scaffolds. Journal of Theoretical Biology, 528, 110852. Read online
18. Browning, A. P., Sharp, J. A., Mapder, T., Baker, C. M., Burrage, K., & Simpson, M. J. (2021). Persistence as an optimal hedging strategy. Biophysical Journal, 120(1), 133-142. Read online
19. Browning, A. P., Sharp, J. A., Murphy, R. J., Gunasingh, G., Lawson, B., Burrage, K., Haass, N. K., & Simpson, M. (2021). Quantitative analysis of tumour spheroid structure. eLife, 10, e73020. Read online
20. Browning, R., Sulem, D., Mengersen, K., Rivoirard, V., & Rousseau, J. (2021). Simple discrete-time self-exciting models can describe complex dynamic processes: A case study of COVID-19. PLOS One, 16(4), e0250015. Read online
21. Burrage, K., Burrage, P., & MacNamara, S. (2021). Localisation and pseudospectra of twisted Toeplitz matrices with applications to ion channels. SIAM Journal on Matrix Analysis and Applications, 42(4), 1656–1679. Read online
22. Burrage, K., Burrage, P., & MacNamara, S. (2021). The reflectionless properties of Toeplitz waves and Hankel waves: An analysis via Bessel functions. Applied Mathematics and Computation, 389, 125576. Read online
23. Beranger, B., Stephenson, A. G., & Sisson, S. A. (2021). High-dimensional inference using the extremal skew-t process. Extremes, 24, 653-685. Read online
24. Callens, A., Wang, Y. - G., Fu, L., & Liquet, B. (2021). Robust Estimation Procedure for Autoregressive Models with Heterogeneity. Environmental Modeling & Assessment, 26, 313 - 323. Read online
25. Camps, J., Lawson, B. A. J., Drovandi, C. C., Minchole, A., Wang, Z. Jenny, Grau, V., Burrage, K., & Rodriguez, B. (2021). Inference of ventricular activation properties from non-invasive electrocardiography. Medical Image Analysis, 73, 102143. Read online
26. Collevecchio, A., & Zeng, X. (2021). A note on recurrence of the Vertex reinforced jump process and fractional moments localization. Electronic Journal of Probability, 26, 63. Read online
27. Collevecchio, A., Hamza, K., & Nguyen, T. - M. (2021). Long range one-cookie random walk with positive speed. Stochastic Processes and their Applications, 142, 462-478. Read online
28. Cui, T., & Zahm, O. (2021). Data-free likelihood-informed dimension reduction of Bayesian inverse problems. Inverse Problems, 37(4), 045009. Read online
29. Cui, Z., Wu, J., Ding, Z., Duan, Q., Lian, W., Yang, Y., & Cao, T. (2021). A hybrid rolling grey framework for short time series modelling. Neural Computing and Applications, 33, 11339-11353. Read online
30. Dandekar, R., Henderson, S. G., Jansen, H. M., McDonald, J., Moka, S., Nazarathy, Y., Rackauckas, C., Taylor, P. G., & Vourinen, A. (2021). Safe Blues: The case for virtual safe virus spread in the long-term fight against epidemics. Patterns, 2(3), 100220. Read online
31. Davoudabadi, M. Javad, Pagendam, D., Drovandi, C., Baldock, J., & White, G. (2021). Advanced Bayesian approaches for state-space models with a case study on soil carbon sequestration. Environmental Modelling & Software, 136, 104919. Read online
32. Dawkins, L. C., Williamson, D. B., Mengersen, K. L., Morawska, L., Jayaratne, R., & Shaddick, G. (2021). Where Is the Clean Air? A Bayesian Decision Framework for Personalised Cyclist Route Selection Using R-INLA. Bayesian Analysis, 16(1), 61-91. Read online
33. de Gier, J., Kenyon, R., & Watson, S. S. (2021). Limit Shapes for the Asymmetric Five Vertex Model. Communications in Mathematical Physics, 385, 793–836. Read online
34. de Gunst, M., Hautphenne, S., Mandjes, M., & Sollie, B. (2021). Parameter estimation for multivariate population processes: a saddlepoint approach. Stochastic Models, 37(1), 168 - 196. Read online
35. De Sterck, H., Falgout, R. D., Friedhoff, S., Krzysik, O. A., & MacLachlan, S. P. (2021). Optimizing multigrid reduction‐in‐time and Parareal coarse‐grid operators for linear advection. Numerical Linear Algebra with Applications, 28(4), e2367. Read online
36. Delaigle, A., Hall, P., Huang, W., & Kneip, A. (2021). Estimating the Covariance of Fragmented and Other Related Types of Functional Data. Journal of the American Statistical Association, 535(116), 1383-1401. Read online
37. Dufays, A., Li, Z., Rombouts, J. V. K., & Song, Y. (2021). Sparse change‐point VAR models. Journal of Applied Econometrics, 36(6), 703-727. Read online
38. Ebert, A., Dutta, R., Mengersen, K., Mira, A., Ruggeri, F., & Wu, P. (2021). Likelihood‐free parameter estimation for dynamic queueing networks: Case study of passenger flow in an international airport terminal. Journal of the Royal Statistical Society: Series C (Applied Statistics), 70(3), 770 - 792. Read online
39. Ebert, A., Mengersen, K., Ruggeri, F., & Wu, P. (2021). Curve Registration of Functional Data for Approximate Bayesian Computation. Stats, 4(3), 762 - 775. Read online
40. Eckert, F., Hyndman, R. J., & Panagiotelis, A. (2021). Forecasting Swiss Exports using Bayesian Forecast Reconciliation. European Journal of Operational Research, 291(2), 693-710. Read online
41. Fackrell, M., Taylor, P., & Wang, J. (2021). Strategic customer behavior in an M/M/1 feedback queue. Queueing Systems, 97(3-4), 223 - 259. Read online
42. Fan, Y., Emvalomenos, G., Grazian, C., & Meikle, S. R. (2021). PET-ABC: fully Bayesian likelihood-free inference for kinetic models. Physics in Medicine & Biology, 66(11), 115002. Read online
43. Fang, S., Deng, Y., & Zhou, Z. (2021). Logarithmic finite-size scaling of the self-avoiding walk at four dimensions. Physical Review E, 104(6), 064108. Read online
44. Fang, S., Zhou, Z., & Deng, Y. (2021). Percolation effects in the Fortuin-Kasteleyn Ising model on the complete graph. Physical Review E, 103(1), 012102. Read online
45. Fehily, Z., Kawasetsu, K., & Ridout, D. (2021). Classifying Relaxed Highest-Weight Modules for Admissible-Level Bershadsky–Polyakov Algebras. Communications in Mathematical Physics, 385(2), 859 - 904. Read online
46. Feng, L., Turner, I., Perré, P., & Burrage, K. (2021). An investigation of nonlinear time-fractional anomalous diffusion models for simulating transport processes in heterogeneous binary media. Communications in Nonlinear Science and Numerical Simulation, 92, 105454. Read online
47. Fitzgerald, S. P., Bean, N. G., Hennessey, J. V., & Falhammar, H. (2021). Thyroid testing paradigm switch from thyrotropin to thyroid hormones—Future directions and opportunities in clinical medicine and research. Endocrine, 74(2), 285 - 289. Read online
48. Forbes, O., Hosking, R., Mokany, K., & Lal, A. (2021). Bayesian spatio-temporal modelling to assess the role of extreme weather, land use change and socio-economic trends on cryptosporidiosis in Australia, 2001–2018. Science of the Total Environment, 791, 148243. Read online
49. Forrester, P., & Li, S. - H. (2021). Fox H-kernel and θ-deformation of the Cauchy Two-Matrix Model and Bures Ensemble. International Mathematics Research Notices, 2021(8), 5791-5824. Read online
50. Forrester, P., & Zhang, J. (2021). Corank-1 projections and the randomised Horn problem. Tunisian Journal of Mathematics, 3(1), 55 - 73. Read online
51. Forrester, P. J. (2021). Circulant L-ensembles in the thermodynamic limit. Journal of Physics A: Mathematical and Theoretical, 54(44), 444003. Read online
52. Forrester, P. J. (2021). Moments of the ground state density for the d-dimensional Fermi gas in an harmonic trap. Random Matrices: Theory and Applications, 10(02), 2150018. Read online
53. Forrester, P. J. (2021). Quantifying Dip–Ramp–Plateau for the Laguerre Unitary Ensemble Structure Function. Communications in Mathematical Physics, 387(1), 215 - 235. Read online
54. Forrester, P. J., & Li, S. - H. (2021). Classical skew orthogonal polynomials in a two-component log-gas with charges +1 and +2. Advances in Mathematics, 383, 107678. Read online
55. Forrester, P. J., & Liu, D. - Z. (2021). Phase Transitions for Products of Characteristic Polynomials under Dyson Brownian Motion. Acta Mathematica Sinica, English Series, 37(3), 509 - 524. Read online
56. Forrester, P. J., & Mazzuca, G. (2021). The classical β-ensembles with β proportional to 1/ N: From loop equations to Dyson’s disordered chain. Journal of Mathematical Physics, 62(7), 073505. Read online
57. Forrester, P. J., & Rahman, A. A. (2021). Relations between moments for the Jacobi and Cauchy random matrix ensembles. Journal of Mathematical Physics, 62(7), 073302. Read online
58. Forrester, P. J., Li, S. - H., & Trinh, A. K. (2021). Asymptotic correlations with corrections for the circular Jacobi β-ensemble. Journal of Approximation Theory, 271, 105633. Read online
59. Frazier, D. T., & Drovandi, C. (2021). Robust approximate Bayesian inference with synthetic likelihood. Journal of Computational and Graphical Statistics, 30(4), 958-976. Read online
60. 60. Garbali, A., & de Gier, J. (2021). The R-Matrix of the Quantum Toroidal Algebra U_q,t(gl₁) in the Fock Module. Communications in Mathematical Physics, 384(3), 1971 - 2008. Read online
61. Gilholm, P., Mengersen, K., & Thompson, H. (2021). Bayesian Hierarchical Multidimensional Item Response Modeling of Small Sample, Sparse Data for Personalized Developmental Surveillance. Educational and Psychological Measurement, 81(5), 936 - 956. Read online
62. Gunawan, D., Griffiths, W., & Chotikapanich, D. (2021). Posterior probabilities for Lorenz and stochastic dominance of Australian income distributions. Economic Record, 97(319), 504-524. Read online
63. Gunawan, D., Kohn, R., & Nott, D. (2021). Variational Bayes approximation of factor stochastic volatility models. International Journal of Forecasting, 37(4), 1355 - 1375. Read online
64. Gundry, L., Guo, S. - X., Kennedy, G., Keith, J., Robinson, M., Gavaghan, D., Bond, A. M., & Zhang, J. (2021). Recent advances and future perspectives for automated parameterisation, Bayesian inference and machine learning in voltammetry. Chemical Communications, 57(15), 1855-1870. Read online
65. Gundry, L., Kennedy, G., Keith, J., Robinson, M., Gavaghan, D., Bond, A. M., & Zhang, J. (2021). A Comparison of Bayesian Inference Strategies for Parameterisation of Large Amplitude AC Voltammetry Derived from Total Current and Fourier Transformed Versions. ChemElectroChem, 8(12), 2238-2258. Read online
66. Halfar, R., Lawson, B. A. J., dos Santos, R. W., & Burrage, K. (2021). Machine Learning Identification of Pro-arrhythmic Structures in Cardiac Fibrosis. Frontiers In Physiology, 12, 709485. Read online
67. Haque, S., Mengersen, K., & Stern, S. (2021). Assessing the accuracy of record linkages with Markov chain based Monte Carlo simulation approach. Journal of Big Data, 8(1), 8. Read online
68. Herath, S., Roughan, M., & Glonek, G. (2021). Generating Name-Like Vectors for Testing Large-Scale Entity Resolution. IEEE Access, 9, 145288 - 145300. Read online
69. Hocagil, T. Akkaya, Cook, R. J., Jacobson, S. W., Jacobson, J. L., & Ryan, L. M. (2021). Propensity score analysis for a semi‐continuous exposure variable: a study of gestational alcohol exposure and childhood cognition. Journal of the Royal Statistical Society: Series A (Statistics in Society), 184(4), 1390 - 1413. Read online
70. 70. Hodgkinson, L., Salomone, R., & Roosta, F. (2021). Implicit Langevin Algorithms for Sampling From Log-concave Densities. Journal of Machine Learning Research, 22(136), 1-30. Read online
71. Holloway-Brown, J., Helmstedt, K. J., & Mengersen, K. L. (2021). Spatial Random Forest (S-RF): A random forest approach for spatially interpolating missing land-cover data with multiple classes. International Journal of Remote Sensing, 42(10), 3756 - 3776. Read online
72. Holloway‐Brown, J., Helmstedt, K. J., & Mengersen, K. L. (2021). Interpolating missing land cover data using stochastic spatial random forests for improved change detection. Remote Sensing in Ecology and Conservation, 7(4), 649 - 665. Read online
73. Hutchins, K. P., Borg, D. N., Bach, A. J. E., Bon, J. J., Minett, G. M., & Stewart, I. B. (2021). Female (Under) Representation in Exercise Thermoregulation Research. Sports Medicine - Open, 7, 43. Read online
74. Hyndman, R. J., Zeng, Y., & Shang, H. Lin. (2021). Forecasting the old‐age dependency ratio to determine a sustainable pension age. Australian & New Zealand Journal of Statistics, 63(2), 241-256. Read online
75. Jacobson, J. L., Akkaya‐Hocagil, T., Ryan, L. M., Dodge, N. C., Richardson, G. A., Olson, H. C., Coles, C. D., Day, N. L., Cook, R. J., & Jacobson, S. W. (2021). Effects of prenatal alcohol exposure on cognitive and behavioral development: Findings from a hierarchical meta‐analysis of data from six prospective longitudinal U.S. cohorts. Alcoholism: Clinical and Experimental Research, 45(10), 2040 - 2058. Read online
76. Jayetileke, H. L., Wang, Y. - G., & Zhu, M. (2021). Predictive regression with p-lags and order-q autoregressive predictors. Journal of Empirical Finance, 62, 282-293. Read online
77. Kandanaarachchi, S., Anantharama, N., & Munoz, M. Andres. (2021). Early detection of vegetation ignition due to powerline faults. IEEE Transactions on Power Delivery, 36(3), 1324 - 1334. Read online
78. Kennedy, D. W., Cameron, J., Wu, P. P. - Y., & Mengersen, K. (2021). Peer groups for organisational learning: Clustering with practical constraints. PLOS One, 16(6), e0251723. Read online
79. Kermorvant, C., Liquet, B., Litt, G., Jones, J. B., Mengersen, K., Peterson, E. E., Hyndman, R. J., & Leigh, C. (2021). Reconstructing Missing and Anomalous Data Collected from High-Frequency In-Situ Sensors in Fresh Waters. International Journal of Environmental Research and Public Health, 18(23), 12803. Read online
80. Kocher, A., Papac, L., Barquera, R., Key, F. M., Spyrou, M. A., Hübler, R., Rohrlach, A. B., Aron, F., Stahl, R., Wissgott, A., van Bömmel, F., Pfefferkorn, M., Mittnik, A., Villalba-Mouco, V., Neumann, G. U., Rivollat, M., van de Loosdrecht, M. S., Majander, K., Tukhbatova, R. I., Musralina, L., Ghalichi, A., Penske, S., Sabin, S., Michel, M., Gretzinger, J., Nelson, E. A., Ferraz, T., Nägele, K., Parker, C., Keller, M., Guevara, E. K., Feldman, M., Eisenmann, S., Skourtanioti, E., Giffin, K., Gnecchi-Ruscone, G. A., Friederich, S., Schimmenti, V., Khartanovich, V., Karapetian, M. K., Chaplygin, M. S., Kufterin, V. V., Khokhlov, A. A., Chizhevsky, A. A., Stashenkov, D. A., Kochkina, A. F., Tejedor-Rodríguez, C., García-Martínez de Lagrán, Í., Arcusa-Magallón, H., Garrido-Pena, R., Royo-Guillén, J. I., Nováček, J., Rottier, S., Kacki, S., Saintot, S., Kaverzneva, E., Belinskiy, A. B., Velemínský, P., Limburský, P., Kostka, M., Loe, L., Popescu, E., Clarke, R., Lyons, A., Mortimer, R., Sajantila, A., Chinique de Armas, Y., Hernandez Godoy, S. T., Hernández-Zaragoza, D. I., Pearson, J., Binder, D., Lefranc, P., Kantorovich, A. R., Maslov, V. E., Lai, L., Zoledziewska, M., Beckett, J. F., Langová, M., Danielisová, A., Ingman, T., Atiénzar, G. G., de Miguel Ibáñez, M. P., Romero, A., Sperduti, A., Beckett, S., Salter, S. J., Zilivinskaya, E. D., Vasil’ev, D. V., von Heyking, K., Burger, R. L., Salazar, L. C., Amkreutz, L., Navruzbekov, M., Rosenstock, E., Alonso-Fernández, C., Slavchev, V., Kalmykov, A. A., Atabiev, B., Batieva, E., Calmet, M. A., Llamas, B., Schultz, M., Krauß, R., Jiménez-Echevarría, J., Francken, M., Shnaider, S., de Knijff, P., Altena, E., Van de Vijver, K., Fehren-Schmitz, L., Tung, T. A.,  Lösch, S., Dobrovolskaya, M., Makarov, N., Read, C., Van Twest, M., Sagona, C., Ramsl, P. C., Akar, M., Yener, K. A., Ballestero, E. C., Cucca, F., Mazzarello, V., Utrilla, P., Rademaker, K., Fernández-Domínguez, E., Baird, D., Semal, P., Márquez-Morfín, L., Roksandic, M., Steiner, H., Salazar-García, D. C., Shishlina, N., Erdal, Y. S., Hallgren, F., Boyadzhiev, Y., Boyadzhiev, K., Küßner, M., Sayer, D., Onkamo, P., Skeates, R., Rojo-Guerra, M., Buzhilova, A., Khussainova, E., Djansugurova, L. B., Beisenov, A. Z., Samashev, Z., Massy, K., Mannino, M., Moiseyev, V., Mannermaa, K., Balanovsky, O., Deguilloux, M. -F., Reinhold, S., Hansen, S., Kitov, E. P., Dobeš, M., Ernée, M., Meller, H., Alt, K. W., Kay Prüfer, K., Warinner, C., Schiffels, S., Stockhammer, P. W., Bos, K., Posth, C., Herbig, A., Haak, W., Krause, J., & Kühnert, D. (2021). Ten millennia of hepatitis B virus evolution. Science, 374(6564), 182 - 188. Read online
81. Kumar, C., Psaltis, S. T. P., Bailleres, H., Turner, I., Brancheriau, L., Hopewell, G., Carr, E. J., Farrell, T., & Lee, D. J. (2021). Accurate estimation of log MOE from non-destructive standing tree measurements. Annals Of Forest Science, 78(1), 8. Read online
82. Lau, C. L., Mayfield, H. J., Sinclair, J. E., Brown, S. J., Waller, M., Enjeti, A. K., Baird, A., Short, K. R., Mengersen, K., & Litt, J. (2021). Risk-benefit analysis of the AstraZeneca COVID-19 vaccine in Australia using a Bayesian network modelling framework. Vaccine, 39(51), 7429 - 7440. Read online
83. Lefèvre, C., & Simon, M. (2021). Schur-Constant and Related Dependence Models, with Application to Ruin Probabilities. Methodology and Computing in Applied Probability, 23(1), 317-339. Read online
84. Li, C., Xie, H. - B., Fan, X., Da Xu, R. Yi, Van Huffel, S., & Mengersen, K. L. (2021). Kernelized Sparse Bayesian Matrix Factorization. IEEE Transactions on Neural Networks and Learning Systems, 32(1), 391 - 404. Read online
85. Li, D., Clements, A., & Drovandi, C. (2021). Efficient Bayesian estimation for GARCH-type models via Sequential Monte Carlo. Econometrics And Statistics, 19, 22-46. Read online
86. Li, H., & Hyndman, R. J. (2021). Assessing mortality inequality in the U.S.: What can be said about the future? Insurance: Mathematics and Economics, 99, 152-162. Read online
87. Liu, C. - J., Wu, J., Jayetileke, H. Lakshika, & Hu, Z. - H. (2021). Long-Range Dependence and Multifractality of Ship Flow Sequences in Container Ports: A Comparison of Shanghai, Singapore, and Rotterdam. Applied Sciences, 11(21), 10378. Read online
88. Liu, Y., & Roosta, F. (2021). Convergence of Newton-MR under Inexact Hessian Information. SIAM Journal on Optimization, 31(1), 59–90. Read online
89. Loaiza-Maya, R., Martin, G. M., & Frazier, D. T. (2021). Focused Bayesian prediction. Journal of Applied Econometrics, 36(5), 517-543. Read online
90. Lui, C. - W., Wang, Z., Wang, N., Milinovich, G., Ding, H., Mengersen, K., Bambrick, H., & Hu, W. (2021). A call for better understanding of social media in surveillance and management of noncommunicable diseases. Health Research Policy and Systems, 19(1), 18. Read online
91. March, N. G., Carr, E. J., & Turner, I. (2021). A fast algorithm for semi-analytically solving the homogenization boundary value problem for block locally-isotropic heterogeneous media. Applied Mathematical Modelling, 92, 23-43. Read online
92. March, N. G., Carr, E. J., & Turner, I. W. (2021). Numerical Investigation into Coarse-Scale Models of Diffusion in Complex Heterogeneous Media. Transport in Porous Media, 139, 467–489. Read online
93. Mays, A., Ponsaing, A., & Schehr, G. (2021). Tracy-Widom Distributions for the Gaussian Orthogonal and Symplectic Ensembles Revisited: A Skew-Orthogonal Polynomials Approach. Journal of Statistical Physics, 182(2), 28. Read online
94. McVinish, R., & Hodgkinson, L. (2021). Fast approximate simulation of finite long-range spin systems. Annals of Applied Probability, 31(3), 1443 - 1473. Read online
95. Mehra, S., McCaw, J. M., Flegg, M. B., Taylor, P. G., & Flegg, J. A. (2021). Antibody Dynamics for Plasmodium vivax Malaria: A Mathematical Model. Bulletin of Mathematical Biology, 83(1), 6. Read online
96. Menictas, M., Nolan, T. H., Simpson, D. G., & Wand, M. (2021). Streamlined variational inference for higher level group-specific curve models. Statistical Modelling, 21(6), 479-519. Read online
97. Miller, M. E., Motti, C. A., Menéndez, P., & Kroon, F. J. (2021). Efficacy of Microplastic Separation Techniques on Seawater Samples: Testing Accuracy Using High-Density Polyethylene. The Biological Bulletin, 240(1), 52 - 66. Read online
98. Montero-Manso, P., & Hyndman, R. J. (2021). Principles and algorithms for forecasting groups of time series: Locality and globality. International Journal of Forecasting, 37(4), 1632-1653. Read online
99. Morota, G., Cheng, H., Cook, D., & Tanaka, E. (2021). Prospects for interactive and dynamic graphics in the era of data-rich animal science. Journal of Animal Science, 99(2), skaa402. Read online
100. Nadarajah, K., Martin, G. M., & Poskitt, D. S. (2021). Optimal bias correction of the log-periodogram estimator of the fractional parameter: A jackknife approach. Journal of Statistical Planning and Inference, 211, 41 - 79. Read online
101. Nguyen, T., Liquet, B., Mengersen, K., & Sous, D. (2021). Mapping of Coral Reefs with Multispectral Satellites: A Review of Recent Papers. Remote Sensing, 13(21), 4470. Read online
102. Pan, S., Zhang, L., Thompson, R. G., & Ghaderi, H. (2021). A parcel network flow approach for joint delivery networks using parcel lockers. International Journal of Production Research, 59(7), 2090 - 2115. Read online
103. Panagiotelis, A., Athanasopoulos, G., Gamakumara, P., & Hyndman, R. J. (2021). Forecast reconciliation: A geometric view with new insights on bias correction. International Journal of Forecasting, 37(1), 343 - 359. Read online
104. Papac, L., Ernée, M., Dobeš, M., Langová, M., Rohrlach, A. B., Aron, F., Neumann, G. U., Spyrou, M. A., Rohland, N., Velemínský, P., Kuna, M., Brzobohatá, H., Culleton, B., Daněček, D., Danielisová, A., Dobisíková, M., Hložek, J., Kennett, D. J., Klementová, J., Kostka, M., Krištuf, P., Kuchařík, M., Hlavová, J. K., Limburský, P., Malyková, D., Mattiello, L., Pecinovská, M., Petriščáková, K., Průchová, E., Stránská, P., Smejtek, L., Špaček, J., Šumberová, R., Švejcar, O., Trefný, M., Vávra, M., Kolář, J., Heyd, V., Krause, J., Pinhasi, R., Reich, D., Schiffels, S., & Haak, W. (2021). Dynamic changes in genomic and social structures in third millennium BCE central Europe. Science Advances, 7(35). Read online
105. Pfiester, L. M., Thompson, R. G., & Zhang, L. (2021). Spatiotemporal exploration of Melbourne pedestrian demand. Journal of Transport Geography, 95, 103151. Read online
106. Psaltis, S., Kumar, C., Turner, I., Carr, E. J., Farrell, T., Brancheriau, L., Bailléres, H., & Lee, D. J. (2021). A new approach for predicting board MOE from increment cores. Annals of Forest Science, 78(3), 78. Read online
107. Purnomo, G. A., Mitchell, K. J., O'Connor, S., Kealy, S., Taufik, L., Schiller, S., Rohrlach, A., Cooper, A., Llamas, B., Sudoyo, H., Teixeira, J. C., & Tobler, R. (2021). Mitogenomes Reveal Two Major Influxes of Papuan Ancestry across Wallacea Following the Last Glacial Maximum and Austronesian Contact. Genes, 12(7), 965. Read online
108. Quella, T. (2021). Symmetry-protected topological phases beyond groups: The q-deformed bilinear-biquadratic spin chain. Physical Review B, 103(5), 054404. Read online
109. Ranathunga, D., Roughan, M., & Nguyen, H. (2021). Mathematical Reconciliation of Medical Privacy Policies. ACM Transactions on Management Information Systems, 12(1), 5. Read online
110. Rohrlach, A. B., Papac, L., Childebayeva, A., Rivollat, M., Villalba-Mouco, V., Neumann, G. U., Penske, S., Skourtanioti, E., van de Loosdrecht, M., Akar, M., Boyadzhiev, K., Boyadzhiev, Y., Deguilloux, M. -F., Dobeš, M., Erdal, Y. S., Ernée, M., Frangipane, M., Furmanek, M., Friederich, S., Ghesquière, E., Hałuszko, A., Hansen, S., Küßner, M., Mannino, M., Özbal, R., Reinhold, S., Rottier, S., Salazar-García, D. C., Diaz, J. S., Stockhammer, P. W., de Togores Muñoz, C. R., Yener, K. A., Posth, C., Krause, J., Herbig, A., & Haak, W. (2021). Using Y-chromosome capture enrichment to resolve haplogroup H2 shows new evidence for a two-path Neolithic expansion to Western Europe. Scientific Reports, 11(1), 15005. Read online
111. Santos‐Fernandez, E., & Mengersen, K. (2021). Understanding the reliability of citizen science observational data using item response models. Methods in Ecology and Evolution, 12(8), 1533-1548. Read online
112. Santos‐Fernandez, E., Peterson, E. E., Vercelloni, J., Rushworth, E., & Mengersen, K. L. (2021). Correcting misclassification errors in crowdsourced ecological data: A Bayesian perspective. Journal of the Royal Statistical Society: Series C (Applied Statistics), 70(1), 147 - 173. Read online
113. Sharp, J. A., Burrage, K., & Simpson, M. J. (2021). Implementation and acceleration of optimal control for systems biology. Journal of the Royal Society Interface, 18(181), 20210241. Read online
114. Spiliotis, E., Abolghasemi, M., Hyndman, R. J., Petropoulos, F., & Assimakopoulos, V. (2021). Hierarchical forecast reconciliation with machine learning. Applied Soft Computing, 112, 107756. Read online
115. Talagala, P. Dilini, Hyndman, R. J., & Smith-Miles, K. (2021). Anomaly Detection in High-Dimensional Data. Journal of Computational and Graphical Statistics, 30(2), 360 - 374. Read online
116. Teo, M., Bean, N. G., & Ross, J. V. (2021). Optimised prophylactic vaccination in metapopulations. Epidemics, 34, 100420. Read online
117. Thamrin, S. A., Aswi, Ansariadi, Jaya, A. K., & Mengersen, K. (2021). Bayesian spatial survival modelling for dengue fever in Makassar, Indonesia. Gaceta Sanitaria, 35(S1), S59 - S63. Read online
118. Tierney, N. J., & Ram, K. (2021). Common-sense approaches to sharing tabular data alongside publication. Patterns, 2(12), 100368. Read online
119. Tran, M. - N., Scharth, M., Gunawan, D., Kohn, R., Brown, S. D., & Hawkins, G. E. (2021). Robustly estimating the marginal likelihood for cognitive models via importance sampling. Behavior Research Methods, 53(3), 1148 - 1165. Read online
120. Ueland, M., Collins, S., Maestrini, L., Forbes, S., & Luong, S. (2021). Fresh vs. frozen human decomposition - a preliminary investigation of lipid degradation products as biomarkers of post-mortem interval. Forensic Chemistry, 24, 100335. Read online
121. Vaisman, R. (2021). Sequential stratified splitting for efficient Monte Carlo integration. Sequential Analysis, 40(3), 314 - 335. Read online
122. Vaisman, R., & Sun, Y. (2021). Reliability and importance measure analysis of networks with shared risk link groups. Reliability Engineering & System Safety, 211, 107578. Read online
123. Weber, D., Nasim, M., Mitchell, L., & Falzon, L. (2021). Exploring the effect of streamed social media data variations on social network analysis. Social Network Analysis and Mining, 11(1), 62. Read online
124. Whebell, R. M., Moroney, T. J., Turner, I. W., Pethiyagoda, R., & McCue, S. W. (2021). Implicit reconstructions of thin leaf surfaces from large, noisy point clouds. Applied Mathematical Modelling, 98, 416 - 434. Read online
125. Whitaker, T., Béranger, B., & Sisson, S. A. (2021). Logistic Regression Models for Aggregated Data. Journal of Computational and Graphical Statistics, 30(4), 1049-1067. Read online
126. Wu, J., Wang, Y. - G., Tian, Y. - C., Burrage, K., & Cao, T. (2021). Support vector regression with asymmetric loss for optimal electric load forecasting. Energy, 223, 119969. Read online
127. Wu, P. Pao- Yen, Babaei, T., O’Shea, M., Mengersen, K., Drovandi, C., McGibbon, K. E., Pyne, D. B., Mitchell, L. J. G., & Osborne, M. A. (2021). Predicting performance in 4 x 200-m freestyle swimming relay events. PLOS One, 16(7), e0254538. Read online
128. Xu, X., McGrory, C. A., Wang, Y. - G., & Wu, J. (2021). Influential factors on Chinese airlines’ profitability and forecasting methods. Journal of Air Transport Management, 91, 101969. Read online
129. Yang, S., Liu, F., Feng, L., & Turner, I. (2021). A novel finite volume method for the nonlinear two-sided space distributed-order diffusion equation with variable coefficients. Journal of Computational and Applied Mathematics, 388, 113337. Read online
130. Yang, Y., Fan, X., Xu, C., Wu, J., & Sun, B. (2021). State consensus cooperative control for a class of nonlinear multi-agent systems with output constraints via ADP approach. Neurocomputing, 458, 284-296. Read online
131. Yao, Z., Xu, P., Roosta, F., & Mahoney, M. W. (2021). Inexact Nonconvex Newton-Type Methods. INFORMS Journal on Optimization, 3(2), 154-182. Read online
132. Zaloumis, S. G., Whyte, J. M., Tarning, J., Krishna, S., McCaw, J. M., Cao, P., White, M. T., Dini, S., Fowkes, F. J. I., Maude, R. J., Kremsner, P., Dondorp, A., Price, R. N., White, N. J., & Simpson, J. A. (2021). Development and validation of an in silico decision-tool to guide optimisation of intravenous artesunate dosing regimens for severe falciparum malaria patients. Antimicrobial Agents and Chemotherapy, 65(6), e02346-20. Read online
133. Zhang, J., Kieburg, M., & Forrester, P. J. (2021). Harmonic analysis for rank-1 randomised Horn problems. Letters in Mathematical Physics, 111(4), 98. Read online
134. Zhang, L., Huang, J., Liu, Z., & Vu, H. L. (2021). An agent-based model for real-time bus stop-skipping and holding schemes. Transportmetrica A: Transport Science, 17(4), 615 - 647. Read online
135. Zhang, M., Liu, F., Turner, I. W., Anh, V. V., & Feng, L. (2021). A finite volume method for the two-dimensional time and space variable-order fractional Bloch-Torrey equation with variable coefficients on irregular domains. Computers & Mathematics with Applications, 98, 81 - 98. Read online
136. Zhang, S., Wu, J., Jia, Y., Wang, Y. - G., Zhang, Y., & Duan, Q. (2021). A temporal LASSO regression model for the emergency forecasting of the suspended sediment concentrations in coastal oceans: Accuracy and interpretability. Engineering Applications of Artificial Intelligence, 100, 104206. Read online
137. Zhang, Y., Bambrick, H., Mengersen, K., Tong, S., & Hu, W. (2021). Using internet-based query and climate data to predict climate-sensitive infectious disease risks: a systematic review of epidemiological evidence. International Journal of Biometeorology, 65(12), 2203 - 2214. Read online
138. Zhu, M., Wu, J., & Wang, Y. ‐G. (2021). Multi‐horizon accommodation demand forecasting: A New Zealand case study. International Journal of Tourism Research, 23(3), 442-453. Read online

Other contribution to refereed journal

1. Parsons, R., Cramb, S. M., & McPhail, S. M. (2021). Clinical prediction models for hospital falls: a scoping review protocol. BMJ Open, 11(9), e051047. Read online

Letter or note

1. Boyle, L. M., Mackay, M., & Stockman, K. (2021). Ambulance ramping, system pressure, and hospitals in crisis: what does the data tell us? Medical Journal of Australia, 215(11), 526-527. Read online
2. Jahan, F., Duncan, E. W., Cramb, S. M., Baade, P. D., & Mengersen, K. L. (2021). Correction to ‘Augmenting disease maps: a Bayesian meta-analysis approach’. Royal Society Open Science, 8(2), 210085. Read online
3. Ryan, L. (2021). Comments on “The Statistician in Medicine” by Austin Bradford Hill. Statistics in Medicine, 40(1), 52-54. Read online

Non-refereed article

1. Bandara, K., Hyndman, R. J., & Bergmeir, C. (2021). MSTL: A Seasonal-Trend Decomposition Algorithm for Time Series with Multiple Seasonal Patterns. Arxiv, arXiv:2107.13462v1. Read online
2. Barbour, A. D., & Lo, T. Y. Y. (2021). The expected degree distributions in transient duplication divergence models. Arxiv, arXiv:2105.14227v1. Read online
3. Bian, L., Cui, T., Yeo, B. T. Thomas, Fornito, A., Razi, A., & Keith, J. M. (2021). Identification of brain states, transitions, and communities using functional MRI. Arxiv, arXiv:2101.10617v1. Read online
4. Chen, Z., de Gier, J., Hiki, I., Sasamoto, T., & Usui, M. (2021). Limiting current distribution for a two species asymmetric exclusion process. Arxiv, arXiv:2104.00026v1. Read online
5. Clisby, N., Conway, A. R., Guttmann, A. J., & Inoue, Y. (2021). Classical length-5 pattern-avoiding permutations. Arxiv, arXiv:2109.13485v1. Read online
6. Conway, A. R., Conway, M., Price, A. Elvey, & Guttmann, A. J. (2021). Pattern-avoiding ascent sequences of length 3. Arxiv, arXiv:2111.01279v1. Read online
7. Cui, T., Dolgov, S., & Zahm, O. (2021). Conditional Deep Inverse Rosenblatt Transports. Arxiv, arXiv:2106.04170v1. Read online
8. Davoudabadi, M. Javad, Pagendam, D., Drovandi, C., Baldock, J., & White, G. (2021). Modelling and predicting soil carbon sequestration: is current model structure fit for purpose? Arxiv, arXiv:2105.04789v1. Read online
9. de Gier, J., Mead, W., & Wheeler, M. (2021). Transition probability and total crossing events in the multi-species asymmetric exclusion process. Arxiv, arXiv:2109.14232v1. Read online
10. di Marco, V., & Keith, J. M. (2021). Sequential Importance Sampling With Corrections For Partially Observed States. Arxiv, arXiv:2103.05217v1. Read online
11. Drovandi, C., & Frazier, D. T. (2021). A Comparison of Likelihood-Free Methods With and Without Summary Statistics. Arxiv, arXiv:2103.02407v1. Read online
12. Duan, Q., McGrory, C. A., Brown, G., Mengersen, K., & Wang, Y. - G. (2021). Spatio-temporal quantile regression analysis revealing more nuanced patterns of climate change: a study of long-term daily temperature in Australia. Arxiv, arXiv:2103.05791v1. Read online
13. Frazier, D. T., Drovandi, C., & Nott, D. J. (2021). Synthetic Likelihood in Misspecified Models: Consequences and Corrections. Arxiv, arXiv:2104.03436v1. Read online
14. Frazier, D. T., Loaiza-Maya, R., & Martin, G. M. (2021). A Note on the Accuracy of Variational Bayes in State Space Models: Inference and Prediction. Arxiv, arXiv:2106.12262v1. Read online
15. Frazier, D. T., Loaiza-Maya, R., & Martin, G. M. (2021). A Note on the Accuracy of Variational Bayes in State Space Models: Inference and Prediction. Arxiv, arXiv:2106.12262v2. Read online
16. Frazier, D. T., Loaiza-Maya, R., Martin, G. M., & Koo, B. (2021). Loss-Based Variational Bayes Prediction. Arxiv, arXiv:2104.14054v1. Read online
17. Frazier, D. T., Renault, E., Zhang, L., & Zhao, X. (2021). Weak Identification in Discrete Choice Models. Arxiv, arXiv:2011.06753v2. Read online
18. Godahewa, R., Bergmeir, C., Webb, G. I., Hyndman, R. J., & Manso, P. M. (2021). Monash Time Series Forecasting Archive. Arxiv, arXiv:2105.06643v1. Read online
19. Guttmann, A., & Kotesovec, V. (2021). L-convex polyominoes and 201-avoiding ascent sequences. Arxiv, arXiv:2109.09928v1. Read online
20. Guttmann, A., & Kotesovec, V. (2021). L-convex polyominoes and 201-avoiding ascent sequences. Arxiv, arXiv:2109.09928v2. Read online
21. Keith, J. M. (2021). Properties of functions on a bounded charge space. Arxiv, arXiv:2106.10894v1. Read online
22. Keith, J. M. (2021). Properties of functions on a bounded charge space. Arxiv, arXiv:2106.10894v2. Read online
23. Keith, J. M., & Markowsky, G. (2021). A theory of integration for Cesàro limits. Arxiv, arXiv:2104.08705v2. Read online
24. Keith, J. M., & Markowsky, G. (2021). Binary sequences with a Cesàro limit. Arxiv, arXiv:2107.01020v1. Read online
25. Kermorvant, C., Liquet, B., Litt, G., Mengersen, K., Peterson, E., Hyndman, R. J., Jones, J. B., & Leigh, C. (2021). Understanding links between water-quality variables and nitrate concentration in freshwater streams using high-frequency sensor data. Arxiv, arXiv:2106.01719v1. Read online
26. Liyanaarachchige, P. Thilan Abe, Fisher, R., Thompson, H., Menendez, P., Gilmour, J., & McGree, J. (2021). Adaptive monitoring of coral health at Scott Reef where data exhibit nonlinear and disturbed trends over time. Authorea. Read online
27. Lo, T. Y. Y. (2021). Weak local limit of preferential attachment random trees with additive fitness. Arxiv, arXiv:2103.00900v1. Read online
28. Lo, T. Y. Y. (2021). Weak local limit of preferential attachment random trees with additive fitness. Arxiv, arXiv:2103.00900v2. Read online
29. Rajapaksha, D., Bergmeir, C., & Hyndman, R. J. (2021) LoMEF: A Framework to Produce Local Explanations for Global Model Time Series Forecasts. Arxiv, arXiv:2111.07001v1. Read online
30. Roughan, M., Herath, S., & Glonek, G. (2021). Em-K Indexing for Approximate Query Matching in Large-scale ER. Arxiv, arXiv:2111.04070v1. Read online
31. Roughan, M., Herath, S., & Glonek, G. (2021). High Performance Out-of-sample Embedding Techniques for Multidimensional Scaling. Arxiv, arXiv:2111.04067v1. Read online
32. Warne, D. J., Baker, R. E., & Simpson, M. J. (2021). Rapid Bayesian inference for expensive stochastic models. Arxiv, arXiv:1909.06540v3. Read online
33. Warne, D. J., Prescott, T. P., Baker, R. E., & Simpson, M. J. (2021). Multifidelity multilevel Monte Carlo to accelerate approximate Bayesian parameter inference for partially observed stochastic processes. Arxiv, arXiv:2110.14082v1. Read online

Invited talks, refereed proceedings and other conference outputs

Full written conference paper (refereed - must be peer reviewed and presented)

1. Degani, E., Maestrini, L., & Bernardi, M. (2021). Model fitting and Bayesian inference via power expectation propagation. 2021 Conference of the Italian Statistical Society (SIS 2021). Virtual: Pearson. Read online
2. Farquhar, M., Burrage, K., & Lawson, B. A. J. (2021). Robust Graph-based Upscaling of Microscale Fibrotic Structures. Computing in Cardiology 2021 (Vol. 48, pp. 1-4). Brno, Czech Republic: IEEE. Read online
3. Gibson, L. J., Jacko, P., Nazarathy, Y., Zhao, Q., & Xia, L. (2021). A Novel Implementation of Q-Learning for the Whittle Index. 14th EAI International Conference, VALUETOOLS 2021 (Vol. 404, pp. 154 - 170). Virtual: Springer. Read online
4. Hodgkinson, L., van der Heide, C., Roosta, F., & Mahoney, M. (2021). Stochastic Continuous Normalizing Flows: Training SDEs as ODEs. Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence (Vol. 161, pp. 1130–1140). Virtual: PMLR. Read online
5. Roosta, F., Hodgkinson, L., van der Heide, C., & Kroese, D. (2021). Shadow Manifold Hamiltonian Monte Carlo. Proceedings of The 24th International Conference on Artificial Intelligence and Statistics (Vol. 130, pp. 1477-1485). San Diego, California: PMLR. Read online
6. Tsuchida, R., Pearce, T., van der Heide, C., Roosta, F., & Gallagher, M. (2021). Avoiding Kernel Fixed Points: Computing with ELU and GELU Infinite Networks. Proceedings of the AAAI Conference on Artificial Intelligence (Vol. 35, pp. 9967-9977). Virtual: AAAI. Read online

Extract of paper (abstracts, extracts and synopses of conference papers that are subsequently published)

1. Abraj, M. (2021). Copula modelling for spatial data: a new approach to model multivariate spatial dependency. 2021 Australian and New Zealand Statistical Conference (ANZSC2021). Virtual.
2. Abraj, M., M Thompson, H., & Wang, Y. - G. (2021). Modelling of Anisotropic Spatial Random Fields Using Mixture Copulas. Early Career & Student Statisticians Conference (ECSSC 2021). Virtual.
3. Baker, P., & Mortlock, M. Y. (2021). Introducing an R Package for Crop Science cropgrowdays: Calculating thermal time, stress days and user defined agro-meteorological variables. 2021 Australian and New Zealand Statistical Conference (ANZSC2021). Virtual.
4. Dang, K. - D., & Maestrini, L. (2021). Variational approximations for structural equation models. Early Career & Student Statisticians Conference (ECSSC 2021). Virtual.
5. Davoudabadi, M. Javad, Pagendam, D., Drovandi, C., Baldock, J., & White, G. (2021). Modelling and predicting soil carbon sequestration: is current model structure fit for purpose? 2021 World Meeting of the International Society for Bayesian Analysis. Virtual. Read online
6. Davoudabadi, M. Javad, Pagendam, D., Drovandi, C., Baldock, J., & White, G. (2021). The application of advanced Bayesian approaches for modeling soil carbon sequestration. 2021 Australian and New Zealand Statistical Conference (ANZSC2021). Virtual.
7. Tierney, N., Cook, D., & Prvan, T. (2021). Tangling is easy but untangling is hard. Some advice on exploratory data analysis for longitudinal data. 2021 Joint Statistical Meetings. Virtual. Read online
8. Whyte, J. M. (2021). Keyword trends for chemicals may lead regulatory response. Could this hint at tomorrow’s (unknown) poisons? Early Career & Student Statisticians Conference (ECSSC 2021). Virtual.
9. Wu, P. Pao- Yen, Ruggeri, F., & Mengersen, K. (2021). Bayesian Network Inference With Uncertain Evidence and Parameters. Bayesian Inference in Stochastic Processes (BISP12). Virtual.

Unpublished presentation or other conference paper (where none of the above categories are met. For example, published on conference website or program.)

1. Asanjarani, A., Nazarathy, Y., & Taylor, P. (2021). A survey of parameter and state estimation in queues: A tutorial. Data Driven Queueing Challenges (DDQC 2021). Virtual.
2. Bon, J. J., Lee, A., & Drovandi, C. (2021). Accelerating sequential Monte Carlo with surrogate likelihoods. 2021 Australian and New Zealand Statistical Conference (ANZSC2021). Virtual.
3. Bon, J. J., Lee, A., & Drovandi, C. (2021). Accelerating sequential Monte Carlo with surrogate likelihoods. 2021 World Meeting of the International Society for Bayesian Analysis (ISBA 2021). Virtual.
4. Boyle, L. (2021). Monitoring overcrowding in a network of hospital emergency departments. 22nd European Young Statisticians Meeting (EYSM 2021). Athens, Greece.
5. Browning, R. (2021). Simple discrete-time self-exciting models can describe complex dynamic processes: A case study of COVID-19. 2021 World Meeting of the International Society for Bayesian Analysis (ISBA 2021). Virtual.
6. Browning, R., & Mengersen, K. (2021). A Bayesian trans-dimensional approach to model Hawkes processes in discrete time. 2021 World Meeting of the International Society for Bayesian Analysis (ISBA 2021). Virtual.
7. Cramb, S. (2021). Geospatial visualisation: the Queensland Injury Atlas. Rural & Remote Road Safety Webinar. Hybrid conference.
8. Cramb, S. M. (2021). TIPS (Ten Incorrect Pithy Statements) for Disease Mapping. Spatial and Temporal Statistics Symposium. Virtual.
9. Dang, K. - D., & Maestrini, L. (2021). Fitting Structural Equation Models via Variational Approximations. 2021 Symposium on Data Science & Statistics. Virtual.
10. de Gier, J. (2021). Transition Probabilities and Expectation Values for Multi-Species Exclusion Processes. Invited Seminar, MSRI. Mathematical Science Research Institute, Berkeley, California.
11. de Gier, J. (2021). Transition probabilities and expectation values for multi-species exclusion processes. 65th Annual Meeting of the Australian Mathematical Society (AustMS 2021). Virtual.
12. Degani, E., Maestrini, L., Toczydlowska, D., & Wand, M. (2021). Streamlined Variational Inference for High Dimensional Mixed Models with Fixed Effects Selection. Australian and New Zealand Statistical Conference (ANZSC 2021). Virtual.
13. Drovandi, C. (2021). A Comparison of Likelihood-Free Methods With and Without Summary Statistics. 2021 World Meeting of the International Society for Bayesian Analysis (ISBA 2021). Virtual.
14. Forbes, O. (2021). Extending Bayesian model averaging methodology for application across multiple unsupervised clustering methods. 2021 Australian and New Zealand Statistical Conference (ANZSC 2021). Virtual.
15. Frazier, D. (2021). Loss-Based Variational Bayes Prediction. 2021 World Meeting of the International Society for Bayesian Analysis (ISBA 2021). Virtual.
16. Grazian, C. (2021). New formulation of the Logistic-Gaussian process to analyse trajectory tracking data. 2021 Australian and New Zealand Statistical Conference (ANZSC 2021). Virtual.
17. Grazian, C., Emvalomenos, G., Fan, Y., & Meikle, S. R. (2021). vPET-ABC: Voxel-wise approximate Bayesian inference for parametric imaging of neurotransmitter release. 2021 IEEE Nuclear Science Symposium and Medical Imaging Conference. Virtual.
18. Grazian, C., Valle, L. Dalla, Liseo, B., & McInner, A. (2021). Approximate Bayesian Conditional Copulas. Bayesian Inference in Stochastic Processes (BISP12). Virtual.
19. Guttmann, A. J. (2021). Classical pattern-avoiding permutations of length 5. Permutation Patterns 2021 Virtual Workshop. Virtual. Read online
20. Guttmann, A. J. (2021). Extracting asymptotics from series coefficients. Lattice Paths, Combinatorics and Interactions. Virtual. Read online
21. Guttmann, T. (2021). Extracting asymptotics from series coefficients. Lattice Paths, Combinatorics and Interactions. Hybrid conference. Read online
22. Guttmann, T. (2021). Non-crossing paths on a lattice. ANZAMP Seminar Series. Virtual.
23. Guttmann, T. (2021). Series analysis applied to several combinatorial problems. Mathematical Physics Group Seminars. The University of Melbourne.
24. Hogg, J. (2021). Modelling cancer risk factors and incidence in Australia. ACEMS Student and ECR Retreat. Virtual.
25. Hogg, J. (2021). Modelling cancer risk factors and incidence in Australia. BRAG Meeting. Queensland University of Technology, Australia.
26. Hogg, J. (2021). Modelling cancer risk factors and incidence in Australia. Data Science HDR Academy Event. Queensland University of Technology, Australia.
27. Huang, W., Delaigle, A., Hall, P., & Kneip, A. (2021). Estimating the covariance of fragmented and other related types of functional data. 4th International Conference on Econometrics and Statistics (EcoSta 2021). Virtual.
28. Hyndman, R. (2021). Probabilistic ensemble forecasting of Australian COVID-19 cases. 2021 Australian and New Zealand Statistical Conference (ANZSC 2021). Virtual.
29. Hyndman, R. J. (2021). Feasts & fables: modern tools for time series analysis. Why R? 2021 Conference. Virtual. Read online
30. Kandanaarachchi, S. (2021). Looking out for anomalies. QUT Mathematics Seminar. Virtual. Read online
31. Kandanaarachchi, S. (2021). Lookout! Persisting anomalies ahead. 2021 Australian and New Zealand Statistical Conference (ANZSC 2021). Virtual.
32. Li, D., Clements, A., & Drovandi, C. (2021). A Bayesian approach for more reliable tail risk forecasts. 4th International Conference on Econometrics and Statistics (EcoSta 2021). Virtual.
33. Maestrini, L., Livieri, G., & Bernardi, M. (2021). Variable Selection for Heteroskedastic Regression Models via Variational Approximations. 2021 World Meeting of the International Society for Bayesian Analysis (ISBA 2021). Virtual.
34. Maestrini, L., Quiroz, M., & Li, F. (2021). Distributed inference for generalized linear models with variable selection. 14th International Conference of the ERCIM WG on Computational and Methodological Statistics (CMStatistics 2021). Virtual.
35. Mengersen, K. (2021). (Not) Aggregating Data. 2021 Australian and New Zealand Statistical Conference (ANZSC 2021). Virtual.
36. Mengersen, K. (2021). AusEnHealth: An Australian Environmental Health Digital Twin. 2nd Ecosystem Change and Population Health Symposium (ECAPH 2021). Virtual.
37. Mengersen, K. (2021). Bayesian Modelling and Analysis of Challenging Data: Describing Systems of Data. P.C. Mahalanobis Memorial Lectures. Virtual.
38. Mengersen, K. (2021). Bayesian Modelling and Analysis of Challenging Data: Finding Patterns in Highly Structured Spatio-Temporal Data. P.C. Mahalanobis Memorial Lectures. Virtual.
39. Mengersen, K. (2021). Bayesian Modelling and Analysis of Challenging Data: Identifying the Intrinsic Dimension of High-Dimensional Data. P.C. Mahalanobis Memorial Lectures. Virtual.
40. Mengersen, K. (2021). Bayesian Modelling and Analysis of Challenging Data: Making New Sources of Data Trustworthy. 2021 Distinguished Lecture Series in Statistical Sciences, Canadian Statistical Sciences Institute (CANSSI). Virtual.
41. Mengersen, K. (2021). Bayesian Modelling and Analysis of Challenging Data: Making New Sources of Data Trustworthy. P.C. Mahalanobis Memorial Lectures. Virtual.
42. Mengersen, K. (2021). Bayesian Modelling of Complicated Systems. Basque Centre for Applied Mathematics - MTB Group - Invited Seminar. Virtual.
43. Mengersen, K. (2021). Better Beliefs: A Bayesian social platform for inclusive and evidence-based decision making. 2021 World Meeting of the International Society for Bayesian Analysis (ISBA 2021). Virtual.
44. Mengersen, K. (2021). Calling all Citizen Scientists: using Bayesian Statistics to advance public input into scientific analysis. Chalmers AI Talk. Virtual.
45. Mengersen, K. (2021). Connecting R to VR: From visualisation to elicitation to illumination. Visualisation Matters 2021. Virtual.
46. Mengersen, K. (2021). Crikey - it's a Bayesian! The David Finney Lecture. Virtual.
47. Mengersen, K. (2021). From Meat Pies to Spaghetti Bolognese. 44th Research Students’ Conference in Probability and Statistics. Virtual.
48. Mengersen, K. (2021). From Meat Pies to Spaghetti Bolognese. Statistical Society of Australia - South Australia Branch - Invited Seminar. Virtual.
49. Mengersen, K. (2021). From Meat Pies to Spaghetti Bolognese: Bayesian Learning in a Big Data World. JCU Lecture Series. Virtual.
50. Mengersen, K. (2021). From Meat Pies to Spaghetti Bolognese: Bayesian Learning in a Big Data World. South African Statistical Association - Invited Seminar. Virtual.
51. Mengersen, K. (2021). Horizons of Bayesian data science. 2021 ANZCA Clinical Trials Network Strategic Research Workshop. Virtual.
52. Mengersen, K. (2021). Let's talk about uncertainty. 2021 IEEE International Conference on Data Mining (ICDM 2021). Virtual.
53. Mengersen, K. (2021). Trajectory 2032 – Is the time right for a National Sport Data Analytics Hub? AIS Sports Technology and Applied Research Symposium (STARS 2021). Virtual.
54. Mengerson, K. (2021). The Origami of Data Science. 63rd ISI World Statistics Congress (ISI 2021). Virtual.
55. Pollett, P., & Hodgkinson, L. (2021). Population networks with no occupancy ceiling. ANZIAM 2021. Virtual.
56. Quiroz, M. (2021). Gaussian variational approximation for high-dimensional state space models. 2021 World Meeting of the International Society for Bayesian Analysis (ISBA 2021). Virtual.
57. Ross, N. (2021). Gaussian process approximation using Stein’s method, with applications to queues. 65th Annual Meeting of the Australian Mathematical Society (AustMS 2021). Virtual.
58. Sainani, K., Wu, P., Mengersen, K., & Johnson, W. (2021). Data Science and Sports Biomechanics Panel. 39th International Society of Biomechanics in Sport Conference. Virtual.
59. Santos-Fernandez, E., Denti, F., Mengersen, K., & Mira, A. (2021). Guard Me If You Can: Revealing the Hidden Dynamics of Sports Interactions Using the Intrinsic Dimension. 2021 Joint Statistical Meetings (JSM 2021). Virtual.
60. Santos-Fernandez, E., Vercelloni, J., Peterson, E., & Mengersen, K. (2021). Data Science meets Citizen Science: how to trust people. 1st International Symposium on the Science of Data Science (ISSDS 2021). Virtual.
61. Schmidt, H. A., Crotty, S. M., & Burgstaller-Muehlbacher, S. (2021). Performance of AIC and BIC to Select Correct Models of Evolution. Society for Molecular Biology and Evolution 2021. Virtual.
62. Simpson, M. (2021). Connecting models and data in mathematical biology. ANZIAM 2021. Virtual.
63. Talagala, T. S. (2021). Feature-based Time Series Forecasting. Why R? 2021 Conference. Virtual. https://www.youtube.com/watch?v=2aRupJEGxGo
64. Taylor, P. (2021). Modelling the Bitcoin blockchain: what can probability and statistics teach us? Early Career & Student Statisticians Conference (ECSSC 2021). Virtual.
65. Taylor, P., & Royston, K. (2021). A call centre server allocation problem. Data Driven Queueing Challenges (DDQC 2021). Virtual.
66. Tierney, N. (2021). Recognising research software in academia. Invited Seminar, UNSW Sydney. Virtual.
67. Tierney, N., Cook, D., & Prvan, T. (2021). Making better spaghetti (plots). ACEMS Student and ECR Retreat. Virtual.
68. Tran, M. - N. (2021). Bayesian computation: why/when Variational Bayes, not MCMC or SMC? Early Career & Student Statisticians Conference (ECSSC 2021). Virtual.
69. Turner, I. (2021). Modelling anomalous diffusion in lignocellulosic biomaterials using a fractional subdiffusion equation. Workshop on the Intersections of Computation and Optimisations. Virtual. Read online
70. Turner, I. (2021). Multiscale modelling of lignocellulosic biomaterials. ANZIAM 2021. Virtual. Read online
71. von Haeseler, A., Burgstaller-Muehlbacher, S., Crotty, S. M., Schmidt, H. A., & Drucks, T. (2021). Model selection on empirical data using deep learning. Society for Molecular Biology and Evolution 2021. Virtual.
72. Warne, D. (2021). An introduction to pseudo-marginal methods for likelihood-free Bayesian inference. Invited Seminar, Wolfson Centre for Mathematical Biology. Virtual.
73. Warne, D. J., Baker, R. E., & Simpson, M. J. (2021). Using model approximations to accelerate Bayesian computation. Early Career & Student Statisticians Conference (ECSSC 2021). Virtual.
74. Warne, D. J., Crossman, K. A., Jin, W., Mengersen, K., Osborne, K., Simpson, M. J., Thompson, A. A., Wu, P., & Ortiz, J. -C. (2021). Identification and modelling of two-phase recovery in hard corals across the Great Barrier Reef. ANZIAM 2021. Virtual.
75. Warne, D. J., Ebert, A., Drovandi, C., & Hu, W. (2021). Modelling the response of communities to COVID-19 outbreaks. 2nd Ecosystem Change and Population Health Symposium (ECAPH 2021). Virtual.
76. Warne, D. J., Ebert, A., Drovandi, C., Hu, W., Mira, A., & Mengersen, K. (2021). Learning from hindsight through stochastic modelling of the global response to the COVID-19 pandemic. 2021 Australian and New Zealand Statistical Conference (ANZSC 2021). Virtual.
77. Warne, D. J., Wu, P., Jin, W., Thompson, A. A., Simpson, M. J., Mengersen, K., & Ortiz, J. - C. (2021). Modelling coral reef recovery for monitoring the health of the Great Barrier Reef. 2021 Australian and New Zealand Statistical Conference (ANZSC 2021). Virtual.
78. Whyte, J. M. (2021). Assessing suitability of a linear switching system for modelling via Monte Carlo consideration of model properties. 5th Engineering Mathematics and Applications Conference. Virtual. Read online
79. Whyte, J. M. (2021). Numerical investigation of structural minimality for structures of uncontrolled linear switching systems with Maple. Maple Conference 2021. Virtual.

Publicly available software

Software and computing packages

1. Baker, P., & Mortlock, M. Y. (2021). Cropgrowdays (v0.1.1). Read online
2. Bon, J. J. (2021). tidytreatment (v0.2.0). Read online
3. Forbes, J., Cook, D., Ebert, A., Hofmann, H., Hyndman, R. J., Lumley, T., Marwick, B., Sievert, C., Sun, M., Talagala, D., Tierney, N., Tomasetti, N., Wang, E., Zhou, F., Commonwealth of Australia AEC, & Australian Bureau of Statistics ABS (2021). eechidna: Exploring Election and Census Highly Informative Data Nationally for Australia (v1.4.1). Read online
4. Grazian, C. (2021). PETabc. Read online
5. H. Zhang, S., Cook, D., Laa, U., Langrené, N., & Menendez, P. (2021). ferrn: Facilitate Exploration of touRR optimisatioN (v0.0.1). Read online
6. Haghbin, H., & Hyndman, R. J. (2021). Rsfar: Seasonal Functional Autoregressive Models (v0.0.1). Read online
7. Harezlak, J., Ruppert, D., & Wand, M. P. (2021). HRW: Datasets, Functions and Scripts for Semiparametric Regression Supporting Harezlak, Ruppert & Wand (2018) (v1.0-5). Read online
8. Hyndman, R. J. (2021). addb: Australian Demographic Data Bank (v3.225). Read online
9. Hyndman, R. J., Athanasopoulos, G., Bergmeir, C., Carceres, G., Chhay, L., O'Hara-Wild, M., Petropoulos, F., Razbash, S., Wang, E., Yasmeen, F., R Core Team, Ihaka, R., Reid, D., Shaub, D., Tang, Y., & Zhou, Z. (2021). forecast: Forecasting Functions for Time Series and Linear Models (v8.15). Read online
10. Hyndman, R. J., Athanasopoulos, G., O'Hara-Wild, M., & RStudio (2021). fpp3: Data for “Forecasting: Principles and Practice” (3rd Edition) (v0.4.0). Read online
11. Hyndman, R. J., Einbeck, J., Wand, M. P., Carrignon, S., & Cheng, F. (2021). hdrcde: Highest Density Regions and Conditional Density Estimation (v3.4). Read online
12. Hyndman, R. J., Gupta, S., Gamakumara, P., Whan, A., Gray, C., Hyndman, T., & Zhang, H. S. (2021). cricketdata: International Cricket Data. Read online
13. Hyndman, R. J., Lee, A., Wang, E., & Wickramasuriya, S. L. (2021). hts: Hierarchical and Grouped Time Series (v6.0.2). Read online
14. Hyndman, R. J., Roberts, J., O'Hara-Wild, M., Tierney, N. J., & Gruer, A. (2021). ozbabynames: Australian Popular Baby Names. Read online
15. Kandanaarachchi, S. (2021). outlierensembles: A Collection of Outlier Ensemble Algorithms (v0.1.0). Read online
16. Kandanaarachchi, S., & Hyndman, R. J. (2021). lookout: Leave One Out Kernel Density Estimates for Outlier Detection (v0.1.0). Read online
17. Lee, S. (2021). liminal: Multivariate Data Visualization with Tours and Embeddings (v0.1.2). Read online
18. Li, W., Cook, D., & Dodwell, E. (2021). spotoroo: Spatiotemporal Clustering of Satellite Hot Spot Data (v0.1.2). Read online
19. Matamoros, A. Alonzo, Nieto-Reyes, A., Hyndman, R. J., O'Hara-Wild, M., & Trapletti, A. (2021). nortsTest: Assessing Normality of Stationary Process (v1.0.3). Read online
20. Matamoros, A. Alonzo, Torres, C. Cruz, Dala, A., Hyndman, R. J., & O'Hara-Wild, M. (2021). bayesforecast: Bayesian Time Series Modeling with Stan (v1.0.1). Read online
21. O'Hara-Wild, M., Hyndman, R. J., & Kinsman, A. (2021). fasster: Fast Additive Switching of Seasonality, Trend and Exogenous Regressors. Read online
22. O'Hara-Wild, M., Hyndman, R. J., Wang, E., Caceres, G., Hensel, T. - G., & Hyndman, T. (2021). fable: Forecasting Models for Tidy Time Series (v0.3.1). Read online
23. O'Hara-Wild, M., Hyndman, R. J., Wang, E., Cook, D., Athanasopoulos, G., & Holt, D. (2021). fabletools: Core Tools for Packages in the 'fable' Framework (v0.3.1). Read online
24. O'Hara-Wild, M., Hyndman, R. J., Wang, E., Cook, D., Talagala, T., & Chhay, L. (2021). feasts: Feature Extraction and Statistics for Time Series (v0.2.2). Read online
25. O'Hara-Wild, M., Hyndman, R. J., Wang, E., Godahewa, R., & Bergmeir, C. (2021). tsibbledata: Diverse Datasets for ’tsibble’ (v0.3.0). Read online
26. O'Hara-Wild, M., Hyndman, R. J., Xie, Y., Krewinkel, A., & Seo, J. Y. (2021). vitae: Curriculum Vitae for R Markdown (v0.4.2). Read online
27. Reynolds, E., Aden-Buie, G., & Tanaka, E. (2021). flipbookr: Parses Code, Creates Partial Code Builds, Delivers Code Movie (v0.1.0). Read online
28. Signorell, A., Aho, K., Alfons, A., Anderegg, N., Aragon, T., Arachchige, C., Arppe, A., Baddeley, A., Barton, K., Bolker, B., Borchers, H. W., Caeiro, F., Champely, S., Chessel, D., Chhay, L., Cooper, N., Cummins, C., Dewey, M., Doran, H. C., Dray, S., Dupont, C., Eddelbuettel, D., Ekstrom, C., Elff, M., Enos, J., Farebrother, R. W., Fox, J., Francois, R., Friendly, M., Galili, T., Gamer, M., Gastwirth, J. L., Gegzna, V., Gel, Y. R., Graber, S., Gross, J., Grothendieck, G., Harrell Jr, F. E., Heiberger, R., Hoehle, M., Hoffmann, C. W., Hojsgaard, S., Hothorn, T., Huerzeler, M., Hui, W. W., Hurd, P., Hyndman, R. J., Jackson, C., Kohl, M., Korpela, M., Kuhn, M., Labes, D., Leisch, F., Lemon, J., Li, D., Maechler, M., Magnusson, A., Mainwaring, B., Malter, D., Marsaglia, G., Marsaglia, J., Matei, A., Meyer, D., Miao, W., Millo, G., Min, Y., Mitchell, D., Mueller, F., Naepflin, M., Navarro, D., Nilsson, H., Nordhausen, K., Ogle, D., Ooi, H., Parsons, N., Pavoine, S., Plate, T., Prendergast, L., Rapold, R., Revelle, W., Rinker, T., Ripley, B. D., Rodriguez, C., Russell, N., Sabbe, N., Scherer, R., Seshan, V. E., Smithson, M., Snow, G., Soetaert, K., Stahel, W. A., Stephenson, A., Stevenson, M., Stubner, R., Templ, M., Lang, D. T., Therneau, T., Tille, Y., Torgo, L., Trapletti, A., Ulrich, J., Ushey, K., VanDerWal, J., Venables, B., Verzani, J., Villacorta Iglesias, P. J., Warnes, G. R., Wellek, S., Wickham, H., Wilcox, R. R., Wolf, P., Wollschlaeger, D., Wood, J., Wu, Y., Yee, T., & Zeileis, A. (2021). DescTools: Tools for Descriptive Statistics (v0.99.44). Read online
29. Sutton, M. (2021). ccpdmp. Read online
30. Talagala, T., Hyndman, R. J., & Athanasopoulos, G. (2021). seer: Feature-Based Forecast Model Selection (v1.1.6). Read online
31. Tanaka, E. (2021). nestr: Build Nesting or Hierarchical Structures (v0.1.2). Read online
32. Tierney, N., & Babu, A. (2021). yahtsee: Yet Another Hierachical Time Series Extension and Expansion. Read online
33. Tierney, N., Golding, N., Babu, A., & Ryan, G. (2021). conmat. Read online
34. Verbesselt, J., Masiliunas, D., Zeileis, A., Hyndman, R. J., Appel, M., Jung, M., Mirt, A., Bernardino, P. N., & Kong, D. (2021). bfast: Breaks for Additive Season and Trend (v1.6.1). Read online
35. Wang, E., Cook, D., Hyndman, R. J., O'Hara-Wild, M., Smith, T., & Davis, W. (2021). tsibble: Tidy Temporal Data Frames and Tools (v1.0.1). Read online
36. Wang, K., Yacobellis, P., Siregar, E., Romanes, S., Fitter, K., Valentino, G., Riva, D., Cook, D., Tierney, N., & Dingorkar, P. (2021). learningtower: OECD PISA Datasets from 2000-2018 in an Easy-to-Use Format (v1.0.0). Read online
37. Warne, D. J. (2021). R Code for Data Processing and Analysis for the Identification of Two-Phase Recovery Patterns using Reef Monitoring Data. Read online
38. Whyte, J. M. (2021). Maple 2020 procedures and a dashboard for interactive testing of uncontrolled linear-time-invariant structures for structural global identifiability. Read online

Data Sets

1. Amaliah, D., Cook, D., & Tanaka, E. (2021). yowie: Longitudinal Wages Data from the National Longitudinal Survey of Youth 1979. Read online
2. Lakshika, J. P. G., & Talagala, T. (2021). MedLEA: Morphological and Structural Features of Medicinal Leaves. Read online
3. Warne, D. J., Crossman, K. A., Jin, W., Mengersen, K., Osborne, K., Simpson, M. J., Thompson, A. A., Wu, P., & Ortiz, J. -C. (2021). Identification of two-phase coral reef recovery patterns. Townsville, QLD: Australian Institute of Marine Science. Read online

Web outputs

1. Stringer, A., & Mengersen, K. (2021). Teaching Tool for Year 12 Mathematical Methods. Read online
2. Stringer, A., & Mengersen, K. (2021). Teaching Tool for Year 12 Specialist Mathematics. Read online
3. Stringer, A., Vercelloni, J., & Mengersen, K. (2021). VRD High School Biology Practical - Web Application. Read online

Technical reports and unrefereed outputs

Unpublished Reports

1. Athanasopoulos, G., Hyndman, R. J., Kourentzes, N., & O'Hara-Wild, M. (2021). Probabilistic forecasts using expert judgement: the road to recovery from COVID-19. Read online
2. Cheng, F., Hyndman, R. J., & Panagiotelis, A. (2021). Manifold learning with approximate nearest neighbours. Read online
3. Gupta, S., Hyndman, R. J., & Cook, D. (2021). Detecting distributional differences between temporal granularities for exploratory time series analysis. Read online
4. Thilan, P., Menendez, P., & McGree, J. M. (2021). Can adaptive design methods capture long-term trends in hard coral cover. Read online
5. Warne, D. J. (2021). ACEMS/AIMS Great Barrier Reef (GBR) Recovery Project – Final Report.