High dimensional discrimination analysis via a semiparametric model

Binyan Jiang; Chenlei Leng

doi:10.1016/j.spl.2015.11.012

High dimensional discrimination analysis via a semiparametric model

Binyan Jiang, Chenlei Leng

Research output: Journal article publication › Journal article › Academic research › peer-review

2 Citations (Scopus)

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
Pages (from-to)	103-110
Number of pages	8
Journal	Statistics and Probability Letters
Volume	110
DOIs	https://doi.org/10.1016/j.spl.2015.11.012
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

More information

10.1016/j.spl.2015.11.012

http://hdl.handle.net/10397/44044

Cite this

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title = "High dimensional discrimination analysis via a semiparametric model",

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.",

keywords = "Bayes rule, Linear discrimination analysis, Monotone transformation, Semiparametric discriminant analysis, Sparsity",

author = "Binyan Jiang and Chenlei Leng",

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AU - Jiang, Binyan

AU - Leng, Chenlei

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N2 - 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.

AB - 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.

KW - Bayes rule

KW - Linear discrimination analysis

KW - Monotone transformation

KW - Semiparametric discriminant analysis

KW - Sparsity

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U2 - 10.1016/j.spl.2015.11.012

DO - 10.1016/j.spl.2015.11.012

M3 - Journal article

SN - 0167-7152

VL - 110

SP - 103

EP - 110

JO - Statistics and Probability Letters

JF - Statistics and Probability Letters

ER -

High dimensional discrimination analysis via a semiparametric model

Abstract

Keywords

ASJC Scopus subject areas

More information

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