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Multiple Temporal Cluster Detection
Author(s) -
Molinari Nicolas,
Bonaldi Chistophe,
Daurés JeanPierre
Publication year - 2001
Publication title -
biometrics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.298
H-Index - 130
eISSN - 1541-0420
pISSN - 0006-341X
DOI - 10.1111/j.0006-341x.2001.00577.x
Subject(s) - resampling , computer science , cluster analysis , variable (mathematics) , cluster (spacecraft) , selection (genetic algorithm) , population , data mining , feature selection , data set , statistics , set (abstract data type) , transformation (genetics) , artificial intelligence , mathematics , medicine , mathematical analysis , biochemistry , environmental health , gene , programming language , chemistry
Summary. This article proposes a simple method to determine single or multiple temporal clustering on a variable size population. By a transformation of the data set, the method based on a regression model allows consideration of a variable population size during the time of study. A model selection procedure and a resampling method are used to select the number of clusters. The results have applications in epidemiological studies of rare diseases.