Abstract: | Direct kernels, due to LAUDER (1983), as an alternative to the indirect kernel method in discriminant analysis are considered. It is shown that direct kernels may be based on any kernel function known in discrete density estimation. The choice of smoothing parameters is based on general loss functions and a family of loss functions which are specific for the discrimination problem is introduced. Examples with distance dependent and distance independent smoothing parameters are given to illustrate the applicability. |