Search for contacts, projects,
courses and publications

New frontiers in Bayesian modeling using the INLA package in R

Additional information

Authors
van Niekerk J., Bakka H., Rue H. ., Schenk O.
Type
Journal Article
Year
forthcoming
Language
English
Abstract
The INLA package provides a tool for computationally efficient Bayesian modeling and inference for various widely used models, more formally the class of latent Gaussian models. It is a non-sampling based framework which provides approximate results for Bayesian inference, using sparse matrices. The swift uptake of this framework for Bayesian modeling is rooted in the computational efficiency of the approach and catalyzed by the demand presented by the big data era. In this paper, we present new developments within the INLA package with the aim to provide a computationally efficient mechanism for the Bayesian inference of relevant challenging situations.
Journal
Journal of Statistical Software
Start page number
1
End page number
27
Keywords
INLA, joint model, non-separable, spatial, temporal, R