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Spatial and spatio-temporal models with R-INLA.

Published on Mar 1, 2013in Spatial and Spatio-temporal Epidemiology
· DOI :10.1016/j.sste.2012.12.001
Marta Blangiardo20
Estimated H-index: 20
(Imperial College London),
Michela Cameletti10
Estimated H-index: 10
+ 1 AuthorsHåvard Rue39
Estimated H-index: 39
(NTNU: Norwegian University of Science and Technology)
Abstract
During the last three decades, Bayesian methods have developed greatly in the field of epidemiology. Their main challenge focusses around computation, but the advent of Markov Chain Monte Carlo methods (MCMC) and in particular of the WinBUGS software has opened the doors of Bayesian modelling to the wide research community. However model complexity and database dimension still remain a constraint. Recently the use of Gaussian random fields has become increasingly popular in epidemiology as very often epidemiological data are characterised by a spatial and/or temporal structure which needs to be taken into account in the inferential process. The Integrated Nested Laplace Approximation (INLA) approach has been developed as a computationally efficient alternative to MCMC and the availability of an R package (R-INLA) allows researchers to easily apply this method. In this paper we review the INLA approach and present some applications on spatial and spatio-temporal data.
  • References (63)
  • Citations (158)
References63
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#1Daniel Simpson (University of Bath)H-Index: 20
#2Janine B. Illian (St And: University of St Andrews)H-Index: 19
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#1Michela Cameletti (University of Bergamo)H-Index: 10
#2Finn Lindgren (NTNU: Norwegian University of Science and Technology)H-Index: 21
Last.Håvard Rue (NTNU: Norwegian University of Science and Technology)H-Index: 39
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#1Giovanna Jona Lasinio (Sapienza University of Rome)H-Index: 13
#2Gianluca Mastrantonio (Sapienza University of Rome)H-Index: 7
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#1Gianluca Baio (UCL: University College London)H-Index: 24
#1Ramiro Ruiz-Cárdenas (UFMG: Universidade Federal de Minas Gerais)H-Index: 4
#2Elias Teixeira Krainski (UFPR: Federal University of Paraná)H-Index: 8
Last.Håvard RueH-Index: 39
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#1Daniel Simpson (NTNU: Norwegian University of Science and Technology)H-Index: 20
#2Finn Lindgren (NTNU: Norwegian University of Science and Technology)H-Index: 21
Last.Håvard Rue (NTNU: Norwegian University of Science and Technology)H-Index: 39
view all 3 authors...
#1Daniel Simpson (NTNU: Norwegian University of Science and Technology)H-Index: 20
#2Finn Lindgren (NTNU: Norwegian University of Science and Technology)H-Index: 21
Last.Håvard Rue (NTNU: Norwegian University of Science and Technology)H-Index: 39
view all 3 authors...
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