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
References in zbMATH (referenced in 9 articles )
Showing results 1 to 9 of 9.
- Wehrhahn, Claudia; Leonard, Samuel; Rodriguez, Abel; Xifara, Tatiana: A Bayesian approach to disease clustering using restricted Chinese restaurant processes (2020)
- Virgilio Gómez-Rubio; Paula Moraga; John Molitor; Barry Rowlingson: DClusterm: Model-Based Detection of Disease Clusters (2019) not zbMATH
- Bivand, Roger S.; Wong, David W. S.: Comparing implementations of global and local indicators of spatial association (2018)
- 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)
- Bilancia, Massimo; Demarinis, Giacomo: Bayesian scanning of spatial disease rates with integrated nested Laplace approximation (INLA) (2014)
- Hossain, Md. Monir; Lawson, Andrew B.: Approximate methods in Bayesian point process spatial models (2009)
- Bivand, Roger S.; Pebesma, Edzer J.; Gómez-Rubio, Virgilio: Applied spatial data analysis with R (2008)
- Sauleau, Erik-A.; Musio, Monica; Etienne, Arnaud; Buemi, Antoine: Comparison of three convolution prior spatial models for cancer incidence (2007)
- Gómez-Rubio, V.; Ferrándiz-Ferragud, J.; López-Quílez, A.: Detecting clusters of disease with R. (2005) ioport