Article ID: | iaor19981887 |
Country: | Netherlands |
Volume: | 74 |
Issue: | 1 |
Start Page Number: | 191 |
End Page Number: | 209 |
Publication Date: | Nov 1997 |
Journal: | Annals of Operations Research |
Authors: | Pavur Robert, Loucopoulos Constantine |
Keywords: | statistics: multivariate |
Although there have been several journal articles on the classificatory performance of mathematical programming approaches to the two-group discriminant problem, there has been no simulation study on the classificatory performance of mathematical programming approaches to the multiple-group problem reported in the literature. This study reports the results of a simulation experiment on the classificatory performance of a single-function and a multiple-function mathematical programming model relative to that of the standard parametric procedures for the three-group problem with small training samples. The effect of second-order terms on the classificatory performance of the mathematical programming models for the three-group problem is also investigated. Furthermore, this study theoretically examines the range of parameter values of a multiple-function mathematical programming model for which its number of misclassifications in the training sample cannot exceed that of a single-function model.