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'))

Peer review:

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

openblascppopenmp

2.70 score 172 downloads 1 exports 3 dependencies

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

TargetResultLatest binary
Doc / VignettesOKJan 27 2025
R-4.5-linux-x86_64NOTEJan 27 2025

Exports:plfd

Dependencies:mathjaxrRcppRcppArmadillo

A Synthetic Example for PLFD

Rendered fromusage.Rmdusingknitr::rmarkdownon Jan 27 2025.

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