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
2021
Lingua
Inglese
Sommario
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.
Parole chiave
INLA, joint model, non-separable, spatial, temporal, R
Periodico
Journal of Statistical Software
Volume
100
Numero ( Mese )
2
Pagine (o numero dell’articolo)
1-28
