Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
1146843 | Journal of Multivariate Analysis | 2009 | 12 Pages |
Abstract
A class of discriminant rules which includes Fisher’s linear discriminant function and the likelihood ratio criterion is defined. Using asymptotic expansions of the distributions of the discriminant functions in this class, we derive a formula for cut-off points which satisfy some conditions on misclassification probabilities, and derive the optimal rules for some criteria. Some numerical experiments are carried out to examine the performance of the optimal rules for finite numbers of samples.
Keywords
Related Topics
Physical Sciences and Engineering
Mathematics
Numerical Analysis
Authors
Hirofumi Wakaki, Makoto Aoshima,