96 citations · 291 across the 19 of their papers we have counts for
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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…
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…
A few statistical principles for data science
Noel Cressie
In any other circumstance, it might make sense to define the extent of the terrain (Data Science) first, and then locate and describe the landmarks (Principles). But this data revo…