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 3 scripts 148 downloads 1 exports 3 dependencies

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

TargetResultDate
Doc / VignettesOKNov 28 2024
R-4.5-linux-x86_64NOTENov 28 2024

Exports:plfd

Dependencies:mathjaxrRcppRcppArmadillo

A Synthetic Example for PLFD

Rendered fromusage.Rmdusingknitr::rmarkdownon Nov 28 2024.

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