Ricerca di contatti, progetti,
corsi e pubblicazioni

New frontiers in Bayesian modeling using the INLA package in R

Informazioni aggiuntive

Autori
van Niekerk J., Bakka H., Rue H. ., Schenk O.
Tipo
Articolo pubblicato in rivista scientifica
Anno
in uscita
Lingua
Inglese
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.
Rivista
Journal of Statistical Software
Pagina inizio
1
Pagina fine
27
Parole chiave
INLA, joint model, non-separable, spatial, temporal, R