4 papers · 1 filter
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…
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…
Scalable skewed Bayesian inference for latent Gaussian models
Shourya Dutta, Janet van Niekerk, Haavard Rue
Approximate Bayesian inference for the class of latent Gaussian models can be achieved efficiently with integrated nested Laplace approximations (INLA). Based on recent reformulati…