DCluster

DCluster: Functions for the detection of spatial clusters of diseases. A set of functions for the detection of spatial clusters of disease using count data. Bootstrap is used to estimate sampling distributions of statistics.

Keywords for this software

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References in zbMATH (referenced in 8 articles )

Showing results 1 to 8 of 8.
Sorted by year (citations)

  1. Wehrhahn, Claudia; Leonard, Samuel; Rodriguez, Abel; Xifara, Tatiana: A Bayesian approach to disease clustering using restricted Chinese restaurant processes (2020)
  2. Virgilio Gómez-Rubio; Paula Moraga; John Molitor; Barry Rowlingson: DClusterm: Model-Based Detection of Disease Clusters (2019) not zbMATH
  3. Bivand, Roger S.; Wong, David W. S.: Comparing implementations of global and local indicators of spatial association (2018)
  4. Aboukhamseen, S. M.; Soltani, A. R.; Najafi, M.: Modelling cluster detection in spatial scan statistics: formation of a spatial Poisson scanning window and an ADHD case study (2016)
  5. Bilancia, Massimo; Demarinis, Giacomo: Bayesian scanning of spatial disease rates with integrated nested Laplace approximation (INLA) (2014)
  6. Hossain, Md. Monir; Lawson, Andrew B.: Approximate methods in Bayesian point process spatial models (2009)
  7. Sauleau, Erik-A.; Musio, Monica; Etienne, Arnaud; Buemi, Antoine: Comparison of three convolution prior spatial models for cancer incidence (2007)
  8. Gómez-Rubio, V.; Ferrándiz-Ferragud, J.; López-Quílez, A.: Detecting clusters of disease with R. (2005) ioport