50 citations · 248 across the 29 of their papers we have counts for
5 papers · 1 filter
deepspat: An R package for modeling nonstationary spatial and spatio-temporal Gaussian and extremes data through deep deformations
Quan Vu, Xuanjie Shao, Raphaël Huser +1
Nonstationarity in spatial and spatio-temporal processes is ubiquitous in environmental datasets, but is not often addressed in practice, due to a scarcity of statistical software…
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-…
Warped Gradient-Enhanced Gaussian Process Surrogate Models for Exponential Family Likelihoods with Intractable Normalizing Constants
Quan Vu, Matthew T. Moores, Andrew Zammit-Mangion
Markov chain Monte Carlo methods for exponential family models with intractable normalizing constant, such as the exchange algorithm, require simulations of the sufficient statisti…
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…
FRK: An R Package for Spatial and Spatio-Temporal Prediction with Large Datasets
Andrew Zammit-Mangion, Noel Cressie
FRK is an R software package for spatial/spatio-temporal modelling and prediction with large datasets. It facilitates optimal spatial prediction (kriging) on the most commonly used…