50 citations · 248 across the 29 of their papers we have counts for
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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…
Deep Compositional Spatial Models
Andrew Zammit-Mangion, Tin Lok James Ng, Quan Vu +1
Spatial processes with nonstationary and anisotropic covariance structure are often used when modelling, analysing and predicting complex environmental phenomena. Such processes ma…
False Discovery Rates to Detect Signals from Incomplete Spatially Aggregated Data
Hsin-Cheng Huang, Noel Cressie, Andrew Zammit-Mangion +1
There are a number of ways to test for the absence/presence of a spatial signal in a completely observed fine-resolution image. One of these is a powerful nonparametric procedure c…