Package: lpda 1.0.1

lpda: Linear Programming Discriminant Analysis

Classification method obtained through linear programming. It is advantageous with respect to the classical developments when the distribution of the variables involved is unknown or when the number of variables is much greater than the number of individuals. LPDA method is published in Nueda, et al. (2022) "LPDA: A new classification method based on linear programming". <doi:10.1371/journal.pone.0270403>.

Authors:Maria Jose Nueda <[email protected]>

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NEWS

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

Peer review:

Datasets:
  • RNAseq - Simulated RNA-Seq dataset example
  • palmdates - Spectrometry and composition chemical of Spanish and Arabian palm dates

On CRAN:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

11 exports 0.00 score 2 dependencies 2 scripts 183 downloads

Last updated 2 years agofrom:3af2546849. Checks:OK: 7. Indexed: yes.

TargetResultDate
Doc / VignettesOKAug 22 2024
R-4.5-winOKAug 22 2024
R-4.5-linuxOKAug 22 2024
R-4.4-winOKAug 22 2024
R-4.4-macOKAug 22 2024
R-4.3-winOKAug 22 2024
R-4.3-macOKAug 22 2024

Exports:bestPCbestVariabilityCVktestCVloolpdalpda.fitlpda.pcalpdaCVPCAstandstand2

Dependencies:Rglpkslam

lpda: Linear Programming Discriminant Analysis

Rendered fromlpdaUsersGuide.Rmdusingknitr::rmarkdownon Aug 22 2024.

Last update: 2023-03-07
Started: 2023-03-07