DClusterm: Model-based detection of disease clusters

by Paula Moraga for R Project for Statistical Computing

Analysis of disease data is important in order to detect disease outbreaks and risk factors. Some of the methods for cluster detection have been implemented in the DCluster package. However, a model-based approach would be of interest in order to explore disease incidence to potential risk factors. Model-based clustering will be implemented using Generalized Linear Models. Hence, many possible clusters will be proposed and the most likely cluster will be selected using model selection techniques