Abstract
We propose a semiparametric linear programming discriminant (SLPD) rule for high dimensional discriminant analysis under a semiparametric model. As an extension, we further propose a two-stage SLPD (TSLPD) rule, which can have better classification performance under mild sparsity assumptions.
Original language | English |
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Pages (from-to) | 103-110 |
Number of pages | 8 |
Journal | Statistics and Probability Letters |
Volume | 110 |
DOIs | |
Publication status | Published - 1 Mar 2016 |
Keywords
- Bayes rule
- Linear discrimination analysis
- Monotone transformation
- Semiparametric discriminant analysis
- Sparsity
ASJC Scopus subject areas
- Statistics and Probability
- Statistics, Probability and Uncertainty