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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>.
| Version: | 1.0.1 |
| Depends: | R (≥ 3.5.0) |
| Imports: | Rglpk |
| Suggests: | rmarkdown, knitr, testthat (≥ 3.0.0) |
| Published: | 2023-03-07 |
| DOI: | 10.32614/CRAN.package.lpda |
| Author: | Maria Jose Nueda |
| Maintainer: | Maria Jose Nueda <mj.nueda at ua.es> |
| License: | GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
| NeedsCompilation: | no |
| Materials: | NEWS |
| CRAN checks: | lpda results |
| Reference manual: | lpda.pdf |
| Vignettes: |
lpda: Linear Programming Discriminant Analysis |
| Package source: | lpda_1.0.1.tar.gz |
| Windows binaries: | r-devel: lpda_1.0.1.zip, r-release: lpda_1.0.1.zip, r-oldrel: lpda_1.0.1.zip |
| macOS binaries: | r-release (arm64): lpda_1.0.1.tgz, r-oldrel (arm64): lpda_1.0.1.tgz, r-release (x86_64): lpda_1.0.1.tgz, r-oldrel (x86_64): lpda_1.0.1.tgz |
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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.