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10/19/2022
Inferring changes to the global carbon cycle with WOMBAT v2.0, a hierarchical flux-inversion framework
The natural cycles of the surface-to-atmosphere fluxes of carbon dioxide...
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09/27/2022
Decisions, decisions, decisions in an uncertain environment
Decision-makers abhor uncertainty, and it is certainly true that the les...
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02/08/2022
Basis-Function Models in Spatial Statistics
Spatial statistics is concerned with the analysis of data that have spat...
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10/06/2021
Modelling, Fitting, and Prediction with Non-Gaussian Spatial and Spatio-Temporal Data using FRK
Non-Gaussian spatial and spatial-temporal data are becoming increasingly...
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07/09/2021
From Many to One: Consensus Inference in a MIP
A Model Intercomparison Project (MIP) consists of teams who each estimat...
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05/15/2021
Spatial Statistics
Spatial statistics is an area of study devoted to the statistical analys...
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02/08/2021
WOMBAT: A fully Bayesian global flux-inversion framework
WOMBAT (the WOllongong Methodology for Bayesian Assimilation of Trace-ga...
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02/03/2021
A few statistical principles for data science
In any other circumstance, it might make sense to define the extent of t...
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04/18/2020
Modeling Nonstationary and Asymmetric Multivariate Spatial Covariances via Deformations
Multivariate spatial-statistical models are useful for modeling environm...
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03/15/2020
Bayesian Inference of Spatio-Temporal Changes of Arctic Sea Ice
Arctic sea ice extent has drawn increasing interest and alarm from geosc...
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05/15/2019
False Discovery Rates to Detect Signals from Incomplete Spatially Aggregated Data
There are a number of ways to test for the absence/presence of a spatial...
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11/21/2017
On statistical approaches to generate Level 3 products from satellite remote sensing retrievals
Satellite remote sensing of trace gases such as carbon dioxide (CO_2) ha...
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11/21/2017
