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FITTING FINITE MIXTURE MODELS IN A REGRESSION CONTEXT
Author(s) -
Jones P.N.,
McLachlan G. J.
Publication year - 1992
Publication title -
australian journal of statistics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.434
H-Index - 41
eISSN - 1467-842X
pISSN - 0004-9581
DOI - 10.1111/j.1467-842x.1992.tb01356.x
Subject(s) - basis (linear algebra) , product (mathematics) , context (archaeology) , cluster (spacecraft) , group (periodic table) , regression analysis , regression , statistics , mode (computer interface) , mathematics , computer science , psychology , artificial intelligence , data mining , econometrics , geography , chemistry , geometry , archaeology , organic chemistry , programming language , operating system
Summary Suppose data are collected in a three‐mode fashion (individuals x items X attributes), and it is sought to cluster the individuals into groups on the basis of lineat relations between scores on the attributes for each item and auxiliary measurements made on the same items. A mixture model is pro posed and the EM algorithm is used to fit it to the data by simultaneously estimating the group parameters and allocating individuals to groups. The method is illustrated by a simulation study and a real example in which consumers are clustered on the basis of product scores that are related to a sensory laboratory measurement.