8 papers
Distributed and recursive Bayesian inference for Big Data and complex spatio-temporal models
Mario Figueira, David Conesa, Antonio López-QuÃlez +1
The rapid growth of massive and complex datasets in fields such as econometrics, environmental sciences, risk management, and public policy has reshaped statistical modeling while…
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…
ADELIA: Automatic Differentiation for Efficient Laplace Inference Approximations
Afif Boudaoud, Lisa Gaedke-Merzhäuser, Alexandros Nikolaos Ziogas +6
Spatio-temporal Bayesian inference drives environmental and health sciences using latent Gaussian models. Integrated Nested Laplace Approximations (INLA) enable inference for these…
Parallel Selected Inversion for Space-Time Gaussian Markov Random Fields
Abylay Zhumekenov, Elias T. Krainski, HÃ¥vard 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…
Accelerated Spatio-Temporal Bayesian Modeling for Multivariate Gaussian Processes
Lisa Gaedke-Merzhäuser, Vincent Maillou, Fernando Rodriguez Avellaneda +5
Multivariate Gaussian processes (GPs) offer a powerful probabilistic framework to represent complex interdependent phenomena. They pose, however, significant computational challeng…
A graphical framework for interpretable correlation matrix models
Anna Freni Sterrantino, Denis Rustand, Janet van Niekerk +2
In this work, we present a new approach for constructing models for correlation matrices with a user-defined graphical structure. The graphical structure makes correlation matrices…