An alternative approach to discriminating multivariate populations and its applications to marketing research |
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Authors: | Sangit Chatterjee A. Narayanan Frederick Wiseman |
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Affiliation: | (1) Department of Management Science, Northeastern University, 02115 Boston, Massachusetts;(2) The Proctor and Gamble Co., 45241 Cincinnati, Ohio;(3) Department of Marketing, Northeastern University, 02115 Boston, Massachusetts |
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Abstract: | A new method for discriminating among multivariate populations, called the Hausdorff procedure, is introduced to the marketing literature. Rules for classification are defined and a limited simulation study is conducted. For the simulation, both the level of collinearity among the discriminating variables and the level of overlap among the populations are varied. The results indicate that this new procedure is particularly suitable when there is either a high degree of collinearity among the predictor variables or considerable overlap of the populations being investigated. The Hausdorff procedure is also applied to two sets of consumer data. In each instance, it is found to be superior to linear discriminant analysis with respect to the percentage of correct classifications. |
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Keywords: | Bootstrap Error rates Hausdorff procedure Hold out sample Leave-one-out Linear discriminant function |
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