Bayesian Detection of Clusters and Discontinuities in Disease Maps
By L. Knorr‐Held, G. Raßer. Biometrics, 2000
309 citations recorded by the source corpus.
Subfields: Artificial Intelligence, Epidemiology, Statistics and Probability
View Paper: https://www.semanticscholar.org/paper/b5aac26d4741a220e83abaecab8a2dcac5d1dfba
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Artificial Intelligence
- Mark F. J. Steel
- Jim E. Griffin
- C. Fernández
- Peter J. Green
- John M. Maheu
- David B. Dunson
- Alan E. Gelfand
- Xin Jin
In Epidemiology
In Statistics and Probability
- Mark F. J. Steel
- Jim E. Griffin
- C. Fernández
- Peter J. Green
- Chris Hans
- John M. Maheu
- Gary Koop
- Philip J. Brown
Citations in the corpus
- Modelling spatially correlated data via mixtures: a Bayesian approach (2002, background): “Further work is needed to draw wider comparisons, which should include other mixture- and partition-based models such as those of Knorr-Held and Rasser (2000) and Green and Richardson (2002), and also variants of the random field models in which the Gaussian assumption is replaced by the use of a…”
- Order-Based Dependent Dirichlet Processes (2006, methodology): “This model has been proposed for general nonlinear regression problems and has been used for spatial mapping problems (e.g., Ferreira, Denison, and Holmes 2002; Knorr-Held and Raßer 2000).”