Package: PLFD 0.2.0

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 (2021, <doi:10.1007/s13171-021-00255-2>).

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

PLFD_0.2.0.tar.gz
PLFD_0.2.0.tar.gz(r-4.5-noble)PLFD_0.2.0.tar.gz(r-4.4-noble)
PLFD_0.2.0.tgz(r-4.4-emscripten)PLFD_0.2.0.tgz(r-4.3-emscripten)
PLFD.pdf |PLFD.html✨
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 181 downloads 1 exports 3 dependencies

Last updated 2 years agofrom:8c4cc80a13. Checks:1 OK, 1 NOTE. Indexed: no.

TargetResultLatest binary
Doc / VignettesOKFeb 26 2025
R-4.5-linux-x86_64NOTEFeb 26 2025

Exports:plfd

Dependencies:mathjaxrRcppRcppArmadillo

A Synthetic Example for PLFD

Rendered fromusage.Rmdusingknitr::rmarkdownon Feb 26 2025.

Last update: 2023-01-10
Started: 2023-01-10