Menu
  • About & Contact
  • Feedback
  • Contribute
  • Help
  • zbMATH

swMATH

swmath-logo
  • Search
  • Advanced search
  • Browse
  • browse software by name
  • browse software by keywords
  • browse software by MSC
  • browse software by types

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

Anything in here will be replaced on browsers that support the canvas element

  • DClusterm
  • areal data
  • software implementations
  • R package
  • global spatial autocorrelation
  • Bayesian statistics
  • spatial statistics
  • model-based spatial scan statistic
  • lattice data
  • ADHD
  • disease clustering
  • Kulldorff-Nagarwalla’s spatial scan statistic
  • spatial clustering
  • cluster detection
  • spatial scan statistics
  • R
  • local spatial autocorrelation
  • Journal of Statistical Software
  • Poisson test
  • prior distribution
  • Chinese restaurant process
  • disease cluster
  • integrated nested Laplace approximation (INLA)

  • URL: cran.r-project.org/web...
  • Code
  • InternetArchive
  • Manual: cran.r-project.org/web...
  • Authors: Virgilio Gómez-Rubio, Juan Ferrándiz-Ferragud, Antonio López-Quílez, Roger Bivand
  • Dependencies: R

  • Add information on this software.


  • Related software:
  • R
  • WinBUGS
  • SpatialEpi
  • latticeExtra
  • rsatscan
  • Pysal
  • spatial
  • PReMiuM
  • reticulate
  • ClustGeo
  • Show more...
  • CrimeStat
  • ncf
  • lme4
  • Surveillance
  • lctools
  • SpatialEpiApp
  • spBayes
  • RColorBrewer
  • rgdal
  • ArcView
  • Show less...

References in zbMATH (referenced in 8 articles )

Showing results 1 to 8 of 8.
y 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

  • Article statistics & filter:

  • Search for articles
  • MSC classification / top
    • Top MSC classes
      • 60 Probability theory and...
      • 62 Statistics
      • 68 Computer science

  • Publication year
    • 2010 - today
    • 2005 - 2009
    • 2000 - 2004
    • before 2000
  • Terms & Conditions
  • Imprint
  • Privacy Policy