44 citations · 45 across the 4 of their papers we have counts for
9 papers
GeoWarp: Warped spatial processes for inferring subsea sediment properties
Michael Bertolacci, Andrew Zammit-Mangion, Juan Valderrama Giraldo +3
For offshore structures like wind turbines, subsea infrastructure, pipelines, and cables, it is crucial to quantify the properties of the seabed sediments at a proposed site. Howev…
Inferring changes to the global carbon cycle with WOMBAT v2.0, a hierarchical flux-inversion framework
Michael Bertolacci, Andrew Zammit-Mangion, Andrew Schuh +5
The natural cycles of the surface-to-atmosphere fluxes of carbon dioxide (CO) and other important greenhouse gases are changing in response to human influences. These changes n…
Basis-Function Models in Spatial Statistics
Noel Cressie, Matthew Sainsbury-Dale, Andrew Zammit-Mangion
Spatial statistics is concerned with the analysis of data that have spatial locations associated with them, and those locations are used to model statistical dependence between the…
WOMBAT: A fully Bayesian global flux-inversion framework
Andrew Zammit-Mangion, Michael Bertolacci, Jenny Fisher +4
WOMBAT (the WOllongong Methodology for Bayesian Assimilation of Trace-gases) is a fully Bayesian hierarchical statistical framework for flux inversion of trace gases from flask, in…
Deep Integro-Difference Equation Models for Spatio-Temporal Forecasting
Andrew Zammit-Mangion, Christopher K. Wikle
Integro-difference equation (IDE) models describe the conditional dependence between the spatial process at a future time point and the process at the present time point through an…
Multi-Scale Process Modelling and Distributed Computation for Spatial Data
Andrew Zammit-Mangion, Jonathan Rougier
Recent years have seen a huge development in spatial modelling and prediction methodology, driven by the increased availability of remote-sensing data and the reduced cost of distr…