Application of model-selection criteria to some problems in multivariate analysis
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A review of model-selection criteria is presented, with a view toward showing their similarities. It is suggested that some problems treated by sequences of hypothesis tests may be more expeditiously treated by the application of model-selection criteria. Consideration is given to application of model-selection criteria to some problems of multivariate analysis, especially the clustering of variables, factor analysis and, more generally, describing a complex of variables.
Key wordsmodel selection model evaluation Akaike's information criterion AIC Schwarz's criterion cluster analysis clustering variables factor analysis
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