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:
lpda_1.0.1.tar.gz
lpda_1.0.1.zip(r-4.5)lpda_1.0.1.zip(r-4.4)lpda_1.0.1.zip(r-4.3)
lpda_1.0.1.tgz(r-4.4-any)lpda_1.0.1.tgz(r-4.3-any)
lpda_1.0.1.tar.gz(r-4.5-noble)lpda_1.0.1.tar.gz(r-4.4-noble)
lpda_1.0.1.tgz(r-4.4-emscripten)lpda_1.0.1.tgz(r-4.3-emscripten)
lpda.pdf |lpda.html✨
lpda/json (API)
NEWS
| # Install 'lpda' in R: |
| install.packages('lpda', repos = c('https://mjnueda.r-universe.dev', 'https://cloud.r-project.org')) |
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 2 years agofrom:3af2546849. Checks:OK: 7. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Nov 20 2024 |
| R-4.5-win | OK | Nov 20 2024 |
| R-4.5-linux | OK | Nov 20 2024 |
| R-4.4-win | OK | Nov 20 2024 |
| R-4.4-mac | OK | Nov 20 2024 |
| R-4.3-win | OK | Nov 20 2024 |
| R-4.3-mac | OK | Nov 20 2024 |
Exports:bestPCbestVariabilityCVktestCVloolpdalpda.fitlpda.pcalpdaCVPCAstandstand2
