Efficient variable screening for multivariate analysis
Journal of Multivariate Analysis
New Fast Algorithms for Error Rate-Based Stepwise Variable Selection in Discriminant Analysis
SIAM Journal on Scientific Computing
Inference for the invariance of canonical analysis under linear transformations
Journal of Multivariate Analysis
Analysis of new variable selection methods for discriminant analysis
Computational Statistics & Data Analysis
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We propose a criterion for variable selection in discriminant analysis. This criterion permits to arrange the variables in decreasing order of adequacy for discrimination, so that the variable selection problem reduces to that of the estimation of suitable permutation and dimensionality. Then, estimators for these parameters are proposed and the resulting method for selecting variables is shown to be consistent. In a simulation study, we compute proportions of correct classification after variable selection in order to gain understanding of the performance of our proposal and to compare it to existing methods.