Bayesian shared spatial-component models to combine and borrow strength across sparse disease surveillance sources-Reference-Cited by-同舟云学术

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Bayesian shared spatial-component models to combine and borrow strength across sparse disease surveillance sources

Published:2012-05 Issue:3 Volume:54 Page:385-404
ISSN:0323-3847
Container-title:Biometrical Journal
language:en
Short-container-title:Biom. J.

Author:

Ancelet Sophie¹,Abellan Juan J.,Del Rio Vilas Víctor J.,Birch Colin²,Richardson Sylvia³

Affiliation:

1. AgroParisTech/INRA UMR518, Department of Applied Mathematics and Informatics (MIA); MORSE team, F-75231 Paris cedex 5; France

2. Veterinary Laboratories Agency; New Haw; Addlestone; Surrey; KT15 3NB; UK

3. Department of Epidemiology and Public Health; Imperial College London; St Mary's Campus, Norfolk Place; London; W2 1PG; UK

Publisher

Wiley

Subject

Statistics, Probability and Uncertainty,General Medicine,Statistics and Probability

Reference47 articles.

1. Evolution of the BSE epidemic in Catalonia (1990-2015) based on a stochastic model;Alba;Veterinary Journal,2010

2. Multiple cancer sites incidence rates estimation using a multivariate Bayesian model;Assunçao;International Journal of Epidemiology,2004

3. Atypical/Nor98 scrapie: properties of the agent, genetics and epidemiology;Benestad;Veterinary Research,2008

4. Spatial interaction and the statistical analysis of lattice systems;Besag;Journal of the Royal Statistical Society, Series B,1974

5. On conditional and intrinsic autoregression;Besag;Biometrika,1995

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