TY - JOUR
T1 - A note on intrinsic conditional autoregressive models for disconnected graphs
AU - Freni-Sterrantino, Anna
AU - Ventrucci, Massimo
AU - Rue, Haavard
N1 - KAUST Repository Item: Exported on 2020-10-01
Acknowledgements: We thank Dr M. A. Vigotti (University of Pisa) for having made available the dataset from the Tuscany Atlas of Mortality 1971–1994. Massimo Ventrucci is supported by the PRIN 2015 grant project n.20154X8K23 (EPHASTAT) founded by the Italian Ministry for Education, University and Research. We can provide the code for the examples.
PY - 2018/5/23
Y1 - 2018/5/23
N2 - In this note we discuss (Gaussian) intrinsic conditional autoregressive (CAR) models for disconnected graphs, with the aim of providing practical guidelines for how these models should be defined, scaled and implemented. We show how these suggestions can be implemented in two examples, on disease mapping.
AB - In this note we discuss (Gaussian) intrinsic conditional autoregressive (CAR) models for disconnected graphs, with the aim of providing practical guidelines for how these models should be defined, scaled and implemented. We show how these suggestions can be implemented in two examples, on disease mapping.
UR - http://hdl.handle.net/10754/626456
UR - http://www.sciencedirect.com/science/article/pii/S1877584517301600
UR - http://www.scopus.com/inward/record.url?scp=85048823942&partnerID=8YFLogxK
U2 - 10.1016/j.sste.2018.04.002
DO - 10.1016/j.sste.2018.04.002
M3 - Article
C2 - 30390932
SN - 1877-5845
VL - 26
SP - 25
EP - 34
JO - Spatial and Spatio-temporal Epidemiology
JF - Spatial and Spatio-temporal Epidemiology
ER -