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07/28/2023
Extremal Dependence of Moving Average Processes Driven by Exponential-Tailed Lévy Noise
Moving average processes driven by exponential-tailed Lévy noise are imp...
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07/23/2023
Robustness, model checking and latent Gaussian models
Model checking is essential to evaluate the adequacy of statistical mode...
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06/26/2023
Locally tail-scale invariant scoring rules for evaluation of extreme value forecasts
Statistical analysis of extremes can be used to predict the probability ...
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04/20/2023
Statistical inference for Gaussian Whittle-Matérn fields on metric graphs
The Whittle-Matérn fields are a recently introduced class of Gaussian pr...
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04/06/2023
Markov properties of Gaussian random fields on compact metric graphs
There has recently been much interest in Gaussian processes on linear ne...
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02/08/2023
Regularity and numerical approximation of fractional elliptic differential equations on compact metric graphs
The fractional differential equation L^β u = f posed on a compact metric...
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11/20/2022
Fitting latent non-Gaussian models using variational Bayes and Laplace approximations
Latent Gaussian models (LGMs) are perhaps the most commonly used class o...
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11/02/2022
Fast Bayesian estimation of brain activation with cortical surface fMRI data using EM
Task functional magnetic resonance imaging (fMRI) is a type of neuroimag...
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09/10/2022
Covariance-based rational approximations of fractional SPDEs for computationally efficient Bayesian inference
The stochastic partial differential equation (SPDE) approach is widely u...
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05/12/2022
Gaussian Whittle-Matérn fields on metric graphs
We define a new class of Gaussian processes on compact metric graphs suc...
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03/10/2022
Controlling the flexibility of non-Gaussian processes through shrinkage priors
The normal inverse Gaussian (NIG) and generalized asymmetric Laplace (GA...
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02/28/2022
Fast Bayesian estimation of brain activation with cortical surface and subcortical fMRI data using EM
Analysis of brain imaging scans is critical to understanding the way the...
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12/19/2021
Realistic and Fast Modeling of Spatial Extremes over Large Geographical Domains
Various natural phenomena exhibit spatial extremal dependence at short d...
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11/01/2021
The SPDE approach for Gaussian and non-Gaussian fields: 10 years and still running
Gaussian processes and random fields have a long history, covering multi...
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06/12/2021
Spatial Bayesian GLM on the cortical surface produces reliable task activations in individuals and groups
The general linear model (GLM) is a popular and convenient tool for esti...
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06/03/2021
Efficient methods for Gaussian Markov random fields under sparse linear constraints
Methods for inference and simulation of linearly constrained Gaussian Ma...
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01/19/2021
Equivalence of measures and asymptotically optimal linear prediction for Gaussian random fields with fractional-order covariance operators
We consider Gaussian measures μ, μ̃ on a separable Hilbert space, with f...
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06/08/2020
The diffusion-based extension of the Matérn field to space-time
The Matérn field is the most well known family of covariance functions u...
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05/27/2020
A spatial template independent component analysis model for subject-level brain network estimation and inference
ICA is commonly applied to fMRI data to extract independent components (...
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05/18/2020
Necessary and sufficient conditions for asymptotically optimal linear prediction of random fields on compact metric spaces
Optimal linear prediction (also known as kriging) of a random field {Z(x...
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12/11/2019
Scale invariant proper scoring rules Scale dependence: Why the average CRPS often is inappropriate for ranking probabilistic forecasts
Averages of proper scoring rules are often used to rank probabilistic fo...
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06/25/2019
Spatial 3D Matérn priors for fast whole-brain fMRI analysis
Bayesian whole-brain functional magnetic resonance imaging (fMRI) analys...
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06/01/2019
Joint spatial modeling of significant wave height and wave period using the SPDE approach
The ocean wave distribution in a specific region of space and time is de...
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03/14/2019
Spatial modeling of significant wave height using stochastic partial differential equations
The general condition of the ocean surface at a certain location in spac...
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04/07/2018
Linear Mixed-Effects Models for Non-Gaussian Repeated Measurement Data
We consider the analysis of continuous repeated measurement outcomes tha...
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02/18/2018
Spatial modelling with R-INLA: A review
Coming up with Bayesian models for spatial data is easy, but performing ...
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11/14/2017
Weak convergence of Galerkin approximations for fractional elliptic stochastic PDEs with spatial white noise
The numerical approximation of the solution u to a stochastic partial di...
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11/12/2017
The SPDE approach for Gaussian random fields with general smoothness
A popular approach for modeling and inference in spatial statistics is t...
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07/07/2016