Publications

The following is a list of publications on work that was partially or fully supported by Australian Research Council (ARC) Discovery Early Career Research Award (DECRA) DE180100203.

2023

• T.L.J. Ng and A. Zammit-Mangion (2023), “Non-homogeneous Poisson process intensity modelling and estimation using measure transport,” Bernoulli, 29(1), 815-838.

• C.K. Wikle and A. Zammit-Mangion (2023), “Statistical Deep Learning for Spatial and Spatio-Temporal Data,” Annual Review of Statistics and Its Application, 10(1), 247-270.

• L. Cartwright, Zammit-Mangion, A. and N. Deutscher (2023), “Emulation of greenhouse-gas sensitivities using variational autoencoders,” Environmetrics, 34(2), e2754.

• Q. Vu, A. Zammit-Mangion, and S. Chuter (2023), “Constructing large nonstationary spatio-temporal covariances via compositional warpings,” Spatial Statistics, 54, 100742.

2022

• A. Zammit-Mangion, T.L.J. Ng, Q. Vu and M. Filippone (2022) “Deep compositional spatial models,” in press with Journal of the American Statistical Association, 117(540), 1787-1808.

• T.L.J. Ng and A. Zammit-Mangion (2022) “Spherical Poisson point process intensity function modeling and estimation with measure transport,” Spatial Statistics, 50, 100629.

• B. Beck, A. Zammit-Mangion, R. Fry, K. Smith, and B. Gabbe (2022), “Spatiotemporal mapping of major trauma in Victoria, Australia,” PLOS One, 17(7):e0266521.

• N. Cressie, M. Bertolacci, and A. Zammit-Mangion (2022), “From many to one: Consensus inference in a MIP,” Geophysical Research Letters, 49, e2022GL098277.

• S. Chuter, A. Zammit-Mangion, J. Rougier, G. Dawson, and J.L. Bamber (2021), “Mass evolution of the Antarctic Peninsula over the last two decades from a joint Bayesian inversion,” The Cryosphere, 16, 1349–1367.

2021

• A. Zammit-Mangion*, M. Bertolacci*, J. Fisher, A. Stavert, M. Rigby, Y. Cao and N. Cressie (2021), “WOMBAT: A fully Bayesian global flux-inversion framework,” in press with Geophysical Model Development. *Contributed equally.

• N. Cressie, M. Sainsbury-Dale and A. Zammit-Mangion (2021), “Basis-function models in spatial statistics,” in press with Annual Review of Statistics and Its Application.

• Q. Vu, A. Zammit-Mangion and N. Cressie (2021) “Modeling nonstationary and asymmetric multivariate spatial covariances via deformations,” in press with Statistica Sinica, doi:10.5705/ss.202020.0156.

• H.-C. Huang, N. Cressie, A. Zammit-Mangion and G. Huang (2021) “False discovery rates to detect signals from incomplete spatially aggregated data,” in press with Journal of Computational and Graphical Statistics, doi:10.1080/10618600.2021.1873144.

• A. Zammit-Mangion and N. Cressie (2021) “FRK: An R package for spatial and spatio-temporal prediction with large datasets,” Journal of Statistical Software, 98(4), 1-48.

• (Discussion) Q. Vu, Y. Cao, J. Jacobson, A. R. Pearse and A. Zammit-Mangion (2021) “Discussion on ‘Competition on Spatial Statistics for Large Datasets’,” Journal of Agricultural, Biological, and Environmental Statistics, https://doi.org/10.1007/s13253-021-00464-0.

2020

• A. Zammit-Mangion and J. Rougier (2020) “Multi-scale process modelling and distributed computation for spatial data,” Statistics and Computing, 30(6), 1609-1627.

• A. Zammit-Mangion and C.K. Wikle (2020) “Deep integro-difference equation models for spatio-temporal forecasting,” Spatial Statistics, 37, 100408.

• E. Yoo, A. Zammit-Mangion and M. Chipeta (2020) “Adaptive spatial sampling design for environmental field prediction using low-cost sensing technologies,” Atmospheric Environment, 221, 117091.

• (Discussion) A. Zammit-Mangion (2020) “Comments on: A high-resolution bilevel skew-t stochastic generator for assessing Saudi Arabia’s wind energy resources,” Environmetrics, e2649, doi:10.1002/env.2649.

2019

• C.K. Wikle, A. Zammit-Mangion and N. Cressie (2019) Spatio-temporal Statistics with R, Boca Raton, FL: Chapman & Hall/CRC.

• T. Suesse and A. Zammit-Mangion (2019) “Marginal maximum likelihood estimation of conditional autoregressive models with missing data,” Stat, 8, e226.

• M.J. Heaton, A. Datta, A. Finley, R. Furrer, J. Guinness, R. Guhaniyogi, F. Gerber, R.B. Gramacy, D. Hammerling, M. Katzfuss, F. Lindgren, D.W. Nychka, F. Sun and A. Zammit-Mangion (2019) “A case study competition among methods for analyzing large spatial data,” Journal of Agricultural, Biological, and Environmental Statistics, 24, pp. 398-425.

• L. Cartwright, A. Zammit-Mangion, S. Bhatia, I. Schroder, F. Phillips, T. Coates, K. Negandhi, T. Naylor, M. Kennedy, S. Zegelin, N. Wokker, N. M. Deutscher and A. Feitz (2019) “Bayesian atmospheric tomography for detection and quantification of methane emissions: Application to data from the 2015 Ginninderra release experiment,” Atmospheric Measurement Techniques, 12, pp. 4659–4676.