A Comparison of Some Parametric and Nonparametric Discrimination Procedures
| Authors | |
|---|---|
| Year of publication | 2002 |
| Type | Article in Proceedings |
| Conference | Summer School DATASTAT 01 Folia Facultatis Scientiarum Naturalium Universitatis Masarykianae Brunensis |
| MU Faculty or unit | |
| Citation | |
| Field | Applied statistics, operation research |
| Keywords | linear and quadratic discriminant analysis; nonparametric discriminant analysis; kernel density estimation; product kernels; bandwidth choice |
| Description | This article compares the performance of parametric and nonparametric discrimination. After a brief description of the discriminant analysis problem the parametric and nonparametric approaches are described. The multivariate product Gaussian and polynomial kernels with various datadriven choices of the bandwidth are used for density estimators and this nonparametric approaches are compared with classical one by some real data. Overall percentages of the misclassification and computer time are used as the measure of performance. |
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