35 citations · 90 across the 12 of their papers we have counts for
13 papers
Cross Validation for the log Gaussian Cox Process
Hans Montcho, Håvard Rue, Finn Lindgren +4
The log Gaussian Cox Process (LGCP) is one of the most widely used models for the analysis of spatial point patterns. Although Bayesian methods and software for fitting LGCPs are n…
Informative Distance-Based Priors for Correlation Matrices Centred on a Target Reference
Anna Freni-Sterrantino, Janet van Niekerk, Elias Teixeira Krainski +3
Specifying a prior over the space of correlation matrices is a persistent challenge in Bayesian analysis. The space is a curved manifold whose dimension grows quadratically with th…
Joint Modeling of Multivariate Longitudinal and Survival Outcomes with the R package INLAjoint
Denis Rustand, Janet van Niekerk, Elias Teixeira Krainski +1
This paper introduces the R package INLAjoint, designed as a toolbox for fitting a diverse range of regression models addressing both longitudinal and survival outcomes. INLAjoint…
Parallel Selected Inversion for Space-Time Gaussian Markov Random Fields
Abylay Zhumekenov, Elias T. Krainski, Håvard Rue
Performing Bayesian inference on large spatio-temporal models requires extracting inverse elements of large sparse precision matrices for marginal variances, as well as estimating…
Non-stationary Bayesian Spatial Model for Disease Mapping based on Sub-regions
Esmail Abdul Fattah, Elias Krainski, Janet van Niekerk +1
This paper aims to extend the Besag model, a widely used Bayesian spatial model in disease mapping, to a non-stationary spatial model for irregular lattice-type data. The goal is t…
Integrated Nested Laplace Approximations for Large-Scale Spatial-Temporal Bayesian Modeling
Lisa Gaedke-Merzhäuser, Elias Krainski, Radim Janalik +2
Bayesian inference tasks continue to pose a computational challenge. This especially holds for spatial-temporal modeling where high-dimensional latent parameter spaces are ubiquito…