A new non-parametric method is recently proposed for discriminant analysis (Sueyoshi, T., 1999. DEA-discriminant analysis in the view of goal programming. European Journal of Operational Research 115, 564–582). The new approach is referred to as “DEA-Discriminant Analysis (DEA-DA)” that is designed to identify the existence of an overlap between two groups, then determining the group membership of a newly sampled observation. A unique feature of the new technique is that it does not assume any discriminant function for group classification. As an extension of his study, this research proposes a new type of DEA-DA, or “Extended DEA-DA”, that can overcome some methodological drawbacks of its original formulation, but simultaneously maintaining its discriminant capabilities. Using a real data set regarding Japanese banks and a large simulation study, this research confirms that the Extended DEA-DA outperforms conventional linear and nonlinear discriminant analysis techniques.
