Linear Programming Discriminant Analysis
Overview
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. Mathematical details behind the method are published in Nueda, et al. (2022) "LPDA: A new classification method based on linear programming". doi:10.1371/journal.pone.0270403.
- March-2026
- In lpda function, establish weights when calling lpda.fit
From NEWS.md in the release
Install
Health
- OK13 OK2026-08-05
- NOTE12 OK, 1 NOTE2026-08-01
- OK13 OK2026-05-11
- WARNING12 OK, 1 WARNING2026-05-10
- OK14 OK2026-03-10
Documentation
- Help pages
- 17
- Examples that run
- 80%4 run in a plain check · 1 only when donttest examples are enabled (R CMD check --as-cran)
- Exported functions with examples
- 56%
- Documented parameters
- 100%
- Return-value docs
- 100%
- Help pages citing references
- 29%
Downloads
Dependencies
Code & Tests
Datasets
People & History
Pick two releases to compare their code metrics.
- RR 4.6.0 released · 2026-04-24
- 1.2.3Latest
- 1.2.22025-10-27 · diff ↗
- 1.2.12025-07-16 · diff ↗
- RR 4.5.0 released · 2025-04-11
- 1.2.02025-03-26 · diff ↗ ·
removed 4 exports
bestVariability, bestPC, CVloo, CVktestadded 2 exports
lpda.3D, lpdaCV.3D - RR 4.4.0 released · 2024-04-24
- RR 4.3.0 released · 2023-04-21
- 1.0.12023-03-07
- RR 4.2.0 released · 2022-04-22
Package metadata
- First published
- 2023-03-07
- Total releases
- 5 / 3 yrs
- License
- GPL (>= 2) OSI
- Minimum R
- ≥ 3.5.0
- Bundled data
- 228 KB / 2 files
- Download size
- 414 KB
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