PLFD: Portmanteau Local Feature Discrimination for Matrix-Variate Data

The portmanteau local feature discriminant approach first identifies the local discriminant features and their differential structures, then constructs the discriminant rule by pooling the identified local features together. This method is applicable to high-dimensional matrix-variate data. See the paper by Xu, Luo and Chen (2021, <doi:10.1007/s13171-021-00255-2>).

Version: 0.2.0
Depends: R (≥ 3.5.0)
Imports: Rcpp (≥ 1.0.2), mathjaxr
LinkingTo: Rcpp (≥ 1.0.2), RcppArmadillo (≥ 0.9.800)
Suggests: knitr, rmarkdown, markdown
Published: 2023-01-10
DOI: 10.32614/CRAN.package.PLFD
Author: Zengchao Xu [aut, cre], Shan Luo [aut], Zehua Chen [aut]
Maintainer: Zengchao Xu <zengc.xu at>
License: GPL-3
NeedsCompilation: yes
Language: en-US
Materials: README NEWS
CRAN checks: PLFD results


Reference manual: PLFD.pdf
Vignettes: PLFD-examples


Package source: PLFD_0.2.0.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): PLFD_0.2.0.tgz, r-oldrel (arm64): PLFD_0.2.0.tgz, r-release (x86_64): PLFD_0.2.0.tgz, r-oldrel (x86_64): PLFD_0.2.0.tgz
Old sources: PLFD archive


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