Elsevier

Handbook of Statistics

Volume 2, 1982, Pages 857-881
Handbook of Statistics

40 Selecting variables in discriminant analysis for improving upon classical procedures

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Publisher Summary

This chapter discusses selecting variables in discriminant analysis for improving upon classical procedures. Standard procedures show often a degrading performance if the number of involved variables is increased beyond a certain bound p. This very interesting phenomenon has been observed by many scientists. Various intrinsically different illustrations can be made because the underlying aims can be different or be specified differently. Of course, the illustrations will also depend upon the underlying parameters and sample sizes. It is interesting to remark that for some completely specified aims holds that the performance of the standard procedure admits different specifications and that even the concept of standard procedure can be doubtful. These variations are of course of almost no importance when compared with the influences of the sample sizes, the underlying parameter and, in particular, the specification of the aim in mind. This phenomenon implies that the standard procedure based on all s variables can often be improved by deleting variables. It depends on the specific aim, performance, values of the underlying parameters and sample sizes that selection of variables should be made.

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