96 citations · 291 across the 19 of their papers we have counts for
22 papers
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…
Decisions, decisions, decisions in an uncertain environment
Noel Cressie
Decision-makers abhor uncertainty, and it is certainly true that the less there is of it the better. However, recognizing that uncertainty is part of the equation, particularly for…
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…
Modelling Big, Heterogeneous, Non-Gaussian Spatial and Spatio-Temporal Data using FRK
Matthew Sainsbury-Dale, Andrew Zammit-Mangion, Noel Cressie
Non-Gaussian spatial and spatio-temporal data are becoming increasingly prevalent, and their analysis is needed in a variety of disciplines. FRK is an R package for spatial/spatio-…
From Many to One: Consensus Inference in a MIP
Noel Cressie, Michael Bertolacci, Andrew Zammit-Mangion
A Model Intercomparison Project (MIP) consists of teams who each estimate the same underlying quantity (e.g., temperature projections to the year 2070), and the spread of the estim…
Spatial Statistics
Noel Cressie, Matthew T. Moores
Spatial statistics is an area of study devoted to the statistical analysis of data that have a spatial label associated with them. Geographers often refer to the "location informat…