Fast Algorithms for Large Scale Generalized Distance Weighted Discrimination
Overview
Solving large scale distance weighted discrimination. The main algorithm is a symmetric Gauss-Seidel based alternating direction method of multipliers (ADMM) method. See Lam, X.Y., Marron, J.S., Sun, D.F., and Toh, K.C. (2018) doi:10.48550/arXiv.1604.05473 for more details.
Install
Health
- OK13 OK2026-08-05
- NOTE12 OK, 1 NOTE2026-08-01
- OK14 OK2026-03-10
Documentation
- Help pages
- 5 (1 internal)includes a package overview page
- Examples that run
- 100%2 run in a plain check
- Exported functions with examples
- 67%
- Documented parameters
- 67%
- Return-value docs
- 67%
- Help pages citing references
- 100%
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Installing DWDLargeR adds no packages beyond those that come with R.
Code & Tests
Datasets
People & History
Previously maintained by Kim-Chuan Toh (0.1-0).
Pick two releases to compare their code metrics.
- RR 4.6.0 released · 2026-04-24
- RR 4.5.0 released · 2025-04-11
- unarchivedReturned to CRAN2024-08-19
- archivedRemoved from CRAN2024-08-19issues were not corrected despite reminders
- 0.2-0Latest
- RR 4.4.0 released · 2024-04-24
- RR 4.3.0 released · 2023-04-21
- RR 4.2.0 released · 2022-04-22
- RR 4.1.0 released · 2021-05-18
- RR 4.0.0 released · 2020-04-24
- RR 3.6.0 released · 2019-04-26
- RR 3.5.0 released · 2018-04-23
- 0.1-02018-02-06
- RR 3.4.0 released · 2017-04-21
Package metadata
- First published
- 2018-02-06
- Total releases
- 2 / 8 yrs
- License
- GPL-2 OSI
- Minimum R
- ≥ 3.5.0
- Bundled data
- 66 KB / 1 file
- Download size
- 60 KB
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