Premium
Theory & Methods: Mixture model clustering using the MULTIMIX program
Author(s) -
Hunt Lynette,
Jorgensen Murray
Publication year - 1999
Publication title -
australian and new zealand journal of statistics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.434
H-Index - 41
eISSN - 1467-842X
pISSN - 1369-1473
DOI - 10.1111/1467-842x.00071
Subject(s) - categorical variable , cluster analysis , multivariate statistics , mathematics , cluster (spacecraft) , missing data , data mining , statistics , computer science , programming language
Hunt (1996) implemented the finite mixture model approach to clustering in a program called MULTIMIX. The program is designed to cluster multivariate data that have categorical and continuous variables and that possibly contain missing values. This paper describes the approach taken to design MULTIMIX and how some of the statistical problems were dealt with. As an example, the program is used to cluster a large medical dataset.