Package: PLFD 0.2.1

Zengchao Xu

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 (2023, <doi:10.1007/s13171-021-00255-2>).

Authors:Zengchao Xu [aut, cre], Shan Luo [aut], Zehua Chen [aut]

PLFD_0.2.1.tar.gz
PLFD_0.2.1.tar.gz(r-4.7-arm64)PLFD_0.2.1.tar.gz(r-4.7-x86_64)PLFD_0.2.1.tar.gz(r-4.6-arm64)PLFD_0.2.1.tar.gz(r-4.6-x86_64)
PLFD_0.2.1.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
PLFD/json (API)
NEWS

# Install 'PLFD' in R:
install.packages('PLFD', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/paradoxical-rhapsody/plfd/issues

Uses libs:
  • openblas– Optimized BLAS
  • c++– GNU Standard C++ Library v3
  • openmp– GCC OpenMP (GOMP) support library

On CRAN:

Conda:

openblascppopenmp

2.70 score 3 scripts 519 downloads 1 exports 3 dependencies

Last updated from:2321e42c3b. Checks:6 OK. Indexed: no.

TargetResultTimeFilesSyslog
linux-devel-arm64OK167
linux-devel-x86_64OK122
source / vignettesOK230
linux-release-arm64OK158
linux-release-x86_64OK125
wasm-releaseOK108

Exports:plfd

Dependencies:mathjaxrRcppRcppArmadillo

A Synthetic Example for PLFD

Rendered fromusage.Rmdusingknitr::rmarkdownon Jun 09 2026.

Last update: 2025-05-20
Started: 2023-01-10