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

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

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.

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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