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
Author: Zengchao Xu [aut, cre], Shan Luo [aut], Zehua Chen [aut]
Maintainer: Zengchao Xu <zengc.xu at aliyun.com>
BugReports: https://github.com/paradoxical-rhapsody/PLFD/issues
License: GPL-3
URL: https://github.com/paradoxical-rhapsody/PLFD
NeedsCompilation: yes
Language: en-US
Materials: README NEWS
CRAN checks: PLFD results

Documentation:

Reference manual: PLFD.pdf
Vignettes: PLFD-examples

Downloads:

Package source: PLFD_0.2.0.tar.gz
Windows binaries: r-devel: PLFD_0.2.0.zip, r-release: PLFD_0.2.0.zip, r-oldrel: PLFD_0.2.0.zip
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
Old sources: PLFD archive

Linking:

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