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2019
Li, D., Clements A., & Drovandi C. (2019).  Efficient Bayesian estimation for GARCH-type models via Sequential Monte Carlo. Bayes on the Beach 2019.
Li, D., Clements A., & Drovandi C. (2019).  Efficient Bayesian Estimation for GARCH-type Models via Sequential Monte Carlo. The 12th International Conference on Monte Carlo Methods and Applications.
Dang, K-D., Quiroz M., Kohn R., Tran M-N., & Villani M. (2019).  Efficient Bayesian inference for large data sets by HMC with energy conserving subsampling. The 10th European Seminar on Bayesian Econometrics.
Priddle, J. W., Sisson S., & Drovandi C. C. (2019).  Efficient Bayesian synthetic likelihood with whitening transformations. arXiv. arXiv:1909.04857v1.
Priddle, J. W., Sisson S., & Drovandi C. C. (2019).  Efficient Bayesian synthetic likelihood with whitening transformations. Bayes on the Beach 2019.
Chin, V., Gunawan D., Fiebig D. G., Kohn R., & Sisson S. (2019).  Efficient data augmentation for multivariate probit models with panel data: An application to general practitioner decision-making about contraceptives. arXiv. arXiv:1806.07274v2.
Guo, L., Zeng F., Turner I., Burrage K., & Karniadakis G. Em (2019).  Efficient Multistep Methods for Tempered Fractional Calculus: Algorithms and Simulations. SIAM Journal on Scientific Computing. 41(4), A2510 - A2535.
Drovandi, C. (2019).  Efficient parameter estimation for complex simulation-based generative models. AutoStat Research Week: Frontiers in Research & Practice in Statistics.
Laub, P. J. (2019).  EMpht.jl.
Herger, N.., Abramowitz G.., Sherwood S.., Knutti R.., Angelil O.., & Sisson S. (2019).  Ensemble optimisation, multiple constraints and overconfidence: a case study with future Australian precipitation change. Climate Dynamics. 53(3-4), 1581-1596.
Beaton, N. R., Bouvel M., Guerrini V., & Rinaldi S. (2019).  Enumerating five families of pattern-avoiding inversion sequences; and introducing the powered Catalan numbers. Theoretical Computer Science. 777, 69 - 92.
Holloway, J. (2019).  Environmental Data in the Development of SDG indicators. 62nd ISI World Statistics Congress.
Vilas, M. P., Adams M. P., Ball M. C., Meynecke J-O., Santini N. S., Swales A., et al. (2019).  Environmental effects on dynamic stem circumference variation in mangrove trees.
Fisher, R., Shiell G. R., Sadler R. J., Inostroza K., Shedrawi G., Holmes T. H., et al. (2019).  epower: An R package for power analysis of Before‐After‐Control‐Impact (BACI) designs. Methods in Ecology and Evolution. 10(11), 1843 - 1853.
Barbour, A.. D., Roellin A., & Ross N. (2019).  Error bounds in local limit theorems using Stein's method. Bernoulli. 25(2), 1076-1104.
Peterson, E., Hoef J. Ver, Hooten M., Hanks E., & Fortin M-J. (2019).  Estimating parameters of landscape resistance using spatial autoregressive models. The 10th International Association for Landscape Ecology World Congress.
Colin, B., & Mengersen KL. (2019).  Estimating Spatial and Temporal Trends in Environmental Indices Based on Satellite Data: A Two-Step Approach. Sensors. 19(2), 361.
Roughan, M., Tuke J., & Parsonage E. (2019).  Estimating the parameters of the Waxman random graph. 16th Workshop on Algorithms and Models for the Web Graph (WAW 2019). 11631, 71-86.
Bean, N. G., Lewis A., & Nguyen G. (2019).  Estimation of Markovian-regime-switching models with independent regimes. arXiv. arXiv:1906.07957v1.
Tierney, N. J., Mira A., H. Reinhold J., Arbia G., Clifford S., Auricchio A., et al. (2019).  Evaluating health facility access using Bayesian spatial models and location analysis methods. (Shah, T. Ikram, Ed.).PLOS ONE. 14(8), e0218310.
Bengston, S.. A., Meissner K.. J., Menviel L.., Sisson S., & Wilkin J.. (2019).  Evaluating the extent of North Atlantic Deep Water and the mean Atlantic δ^{13}C from statistical reconstructions. Paleoceanography and Paleoclimatology. 34(6), 1022-1036.
Aswi, A.., Cramb S., Hu W., White G., & Mengersen KL. (2019).  Evaluating the interplay between clusters, climatic covariates and spatial priors in spatio-temporal modelling of dengue in Makassar, Indonesia. Bayes on the Beach 2019.
Sarker, C., Mejias L., Maire F., & Woodley A. (2019).  Evaluation of the Impact of Image Spatial Resolution in Designing a Context-Based Fully Convolution Neural Networks for Flood Mapping. 2019 Digital Image Computing: Techniques and Applications (DICTA).
Kandanaarachchi, S. (2019).  eventstream.
Chan, C., Aleti A., Heger A., & Smith-Miles K. (2019).  Evolving stellar models to find the origins of our galaxy. the Genetic and Evolutionary Computation ConferenceProceedings of the Genetic and Evolutionary Computation Conference on - GECCO '19. 1129 - 1137.
Beaton, N.. R., Owczarek A.. L., & Rechnitzer A.. (2019).  Exact Solution of Some Quarter Plane Walks with Interacting Boundaries. The Electronic Journal of Combinatorics. 26(3), P3.53.
Kaur, S., Horne A. C., Nathan R., Szemis J. M., Gibson L., Costa A. M., et al. (2019).  Examining Trade-Offs in Piggybacking Flow Events while Making Environmental Release Decisions in a River System. Journal of Water Resources Planning and Management. 145(6), 04019019.
Tsuchida, R., Roosta F., & Gallagher M. (2019).  Exchangeability and Kernel Invariance in Trained MLPs. (Kraus, S., & Eiter T., Ed.).Twenty-Eighth International Joint Conference on Artificial Intelligence. 3592 - 3598.
Cameron, J., Kennedy D., & Mengersen KL. (2019).  Executive Summary of the Benchmarking Project.
Bednarz, T. (2019).  Expanded Perception. The 16th International Conference on Computer Graphics, Imaging and Visualization (IV/CGiV 2019).
Bednarz, T. (2019).  Expanded Perception and Interaction for Measurement Scienc. APMP 2019 Symposium at the 35th Asia Pacific Metrology Programme General Assembly and Related Meetings..
Bednarz, T.. (2019).  Expended Perception and Interaction. 16th International Conference Computer Graphics, Imaging and Visualization.
Bui, Q., Bergmeir C., Vahid F., & Hyndman R. J. (2019).  Exploratory Analysis of Waterloo Wind Farm's WTGs.
Tierney, N., & Cook D. (2019).  Exploring and understanding the individual experience from longitudinal data, or ... How to make better spaghetti (plots). OzViz 2019.
Tierney, N., & Cook D. (2019).  Exploring and understanding the individual experience from longitudinal data, or ... How to make better spaghetti (plots). Research School of Finance, Actuarial Studies & Statistics Seminar.
Montero-Manso, P. (2019).  Exploring Functional Temporal Data. XXXVIII Spanish Conference on Statistics and Operational Research.
TAN, Y.., Zhang L., CHU T.., & WU L.. (2019).  EXPLORING PEDESTRIAN COUNTS IN A LARGE CENTRAL CITY AREA. THE 24TH INTERNATIONAL CONFERENCE OF HONG KONG SOCIETY FOR TRANSPORTATION STUDIES.
Vercelloni, J., Kayal M., Chancerelle Y., & Planes S. (2019).  Exposure, vulnerability, and resiliency of French Polynesian coral reefs to environmental disturbances. Scientific Reports. 9(1), 1027.
[Anonymous] (2019).  Expressive Priors in Bayesian Neural Networks: Kernel Combinations and Periodic Functions.
Braunsteins, P., & Hautphenne S. (2019).  Extinction in lower Hessenberg branching processes with countably many types. The Annals of Applied Probability. 29(5), 2782 - 2818.
Thiele, S. T., Grose L., Cui T., Cruden A. R., & Micklethwaite S. (2019).  Extraction of high-resolution structural orientations from digital data: A Bayesian approach. Journal of Structural Geology. 122, 106 - 115.
Béranger, B.., Padoan S.A.., Xu Y.., & Sisson S. (2019).  Extremal properties of the multivariate extended skew-normal distribution, Part B. Statistics & Probability Letters. 147, 105 - 114.
Béranger, B.., Padoan S.A.., Xu Y.., & Sisson S. (2019).  Extremal properties of the univariate extended skew-normal distribution, Part A. Statistics & Probability Letters. 147, 73 - 82.
Hyndman, R. J., Wang E., O'Hara-Wild M., Cook D., & Caceres G. (2019).  fable: Forecasting Models for Tidy Time Series.
O'Hara-Wild, M., Hyndman R. J., Wang E., & Caceres G. (2019).  fable: Forecasting Models for Tidy Time Series.
O'Hara-Wild, M., Hyndman R. J., Wang E., Cook D., & Athanasopoulos G. (2019).  fabletools: Core Tools for Packages in the 'fable' Framework.
Hyndman, R. J., & Wang E. (2019).  fabletools: Core Tools for Packages in the 'fable' Framework.
Yu, J. (2019).  Fast and Accurate Frequentist Generalised Linear Mixed Model Analysis via Expectation Propagation. 2019 ACEMS Enabling Algorithms Theme Symposium.
Ridall, G.., George M.., & PETTITT A.. N. (2019).  Fast sequential Bayesian analysis of football scores illustrating the evolution of the styles and strengths of each of the British premier league football sides over two decades. 34th International Workshop on Statistical Modeling. 2, 267-272.
Gander, P., O’Keeffe K., Santos-Fernández E., Huntington A., Walker L., & Willis J. (2019).  Fatigue and nurses’ work patterns: An online questionnaire survey. International Journal of Nursing Studies. 98, 67–74.

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