Imperial College London


Faculty of MedicineSchool of Public Health

Chair in Biostatistics



m.blangiardo Website




528Norfolk PlaceSt Mary's Campus






BibTex format

author = {Blangiardo, M and Cameletti, M},
doi = {10.1002/9781118950203},
title = {Spatial and Spatio-temporal Bayesian Models with R - INLA},
url = {},
year = {2015}

RIS format (EndNote, RefMan)

AB - © 2015 John Wiley & Sons, Ltd. All rights reserved. Spatial and Spatio-Temporal Bayesian Models with R-INLA provides a much needed, practically oriented & innovative presentation of the combination of Bayesian methodology and spatial statistics. The authors combine an introduction to Bayesian theory and methodology with a focus on the spatial and spatio-temporal models used within the Bayesian framework and a series of practical examples which allow the reader to link the statistical theory presented to real data problems. The numerous examples from the fields of epidemiology, biostatistics and social science all are coded in the R package R-INLA, which has proven to be a valid alternative to the commonly used Markov Chain Monte Carlo simulations. o
AU - Blangiardo,M
AU - Cameletti,M
DO - 10.1002/9781118950203
PY - 2015///
SN - 9781118326558
TI - Spatial and Spatio-temporal Bayesian Models with R - INLA
UR -
ER -