1 citations · 4 across the 20 of their papers we have counts for
24 papers
Flexible covariance structures on metric graphs
Karina Lilleborge, Sara Martino, Geir-Arne Fuglstad
Whittle-Matérn (WM) Gaussian random fields (GRFs) are defined as solutions of stochastic partial differential equations (SPDEs) and provide a natural analog of Matérn GRFs on non-E…
Sampling distributions for complex design variance estimators in a Fay-Herriot model
Alana McGovern, Geir-Arne Fuglstad, Jon Wakefield
Fay-Herriot (FH) models with variance smoothing typically use chi-squared sampling distributions for the design variance estimators. This choice is only valid under strong assumpti…
ARMA approximation of a Non-separable Spatio-Temporal Model with Fractional Smoothnesses in Space and Time
S. Knutsen Furset, Geir-Arne Fuglstad, Espen R. Jakobsen
The Matérn covariance model is ubiquitous in spatial modelling, but there is no default choice for spatio-temporal modelling. In this paper, we consider the recently proposed ``dif…
Non-stationary Spatial Modeling Using Fractional SPDEs
Elling Svee, Geir-Arne Fuglstad
We construct a Gaussian random field (GRF) that combines fractional smoothness with spatially varying anisotropy. The GRF is defined through a stochastic partial differential equat…
Surface finite element approximation of parabolic SPDEs with Whittle--Matérn noise
Øyvind Stormark Auestad, Geir-Arne Fuglstad, Annika Lang
We propose and analyse a new type of fully discrete surface finite element approximation of a class of linear parabolic stochastic evolution equations with additive noise. Our disc…
Joint Modelling of Line and Point Data on Metric Graphs
Karina Lilleborge, Sara Martino, Geir-Arne Fuglstad +2
Metric graphs are useful tools for describing spatial domains like road and river networks, where spatial dependence act along the network. We take advantage of recent developments…