7 papers · 1 filter
A bridge representation of Gaussian Whittle-Matérn fields on compact metric graphs
David Bolin, Alexandre B. Simas, Jonas Wallin
Gaussian Whittle-Matérn fields form a flexible class of Gaussian processes on compact metric graphs, where spatial dependence is governed by the geometry and connectivity of the ne…
Operator-matched spatial regression
David Bolin
A standard spatial regression model , with covariates and a Gaussian random field with Matérn covariance, decouples covariate effects from spatial dependenc…
Gaussian Processes on Directed Metric Graphs
David Bolin, Alexandre de Bustamante Simas, Erik Karlsson Strandh +1
We introduce a statistical framework for Gaussian fields indexed at arbitrary edge locations on general compact directed metric graphs. The construction is based on a stochastic di…
Modeling Spatially Obfuscated Street-Crime Data using Log-Gaussian Cox Processes on Metric Graphs
Lulu Jiang, David Bolin
We develop a log-Gaussian Cox process framework for modelling street-level crime data observed on a road network when the released event locations are spatially obfuscated. Motivat…
Mass Lumping and Numerical Quadrature for Approximation of Fractional Elliptic Differential Equations Driven by Gaussian White Noise
Kelvin J. R. Almeida-Sousa, David Bolin, Alexandre B. Simas
Fractional elliptic stochastic partial differential equations (SPDEs) are widely used in statistics and machine learning for computationally efficient and flexible modeling of Gaus…
Finite element and box-method discretizations for fractional elliptic problems with quadrature and mass lumping
Kelvin J. R. Almeida-Sousa, David Bolin, Alexandre B. Simas
We analyze numerical approximation of the fractional elliptic problem , , where is a second-order self-adjoint elliptic operator with homogeneous Dirichlet or Ne…
Geometric ergodicity of Gibbs samplers for linear latent models with GIG variance mixtures
Elsiddig Awadelkarim, David Bolin, Xiaotian Jin +2
We study geometric ergodicity of the Gibbs sampler for linear latent non-Gaussian models (LLnGMs), a class of hierarchical models in which conditional Gaussian structure is preserv…