DWDLargeR: Fast Algorithms for Large Scale Generalized Distance Weighted Discrimination

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.

Version: 0.1-0
Depends: R (≥ 2.10), Matrix, SparseM
Imports: methods, stats
Published: 2018-02-06
DOI: 10.32614/CRAN.package.DWDLargeR
Author: Xin-Yee Lam, J.S. Marron, Defeng Sun, and Kim-Chuan Toh
Maintainer: Kim-Chuan Toh <mattohkc at nus.edu.sg>
License: GPL-2
URL: https://arxiv.org/pdf/1604.05473.pdf
NeedsCompilation: no
CRAN checks: DWDLargeR results [issues need fixing before 2024-07-31]


Reference manual: DWDLargeR.pdf


Package source: DWDLargeR_0.1-0.tar.gz
Windows binaries: r-devel: DWDLargeR_0.1-0.zip, r-release: DWDLargeR_0.1-0.zip, r-oldrel: DWDLargeR_0.1-0.zip
macOS binaries: r-release (arm64): DWDLargeR_0.1-0.tgz, r-oldrel (arm64): DWDLargeR_0.1-0.tgz, r-release (x86_64): DWDLargeR_0.1-0.tgz, r-oldrel (x86_64): DWDLargeR_0.1-0.tgz

Reverse dependencies:

Reverse imports: diproperm


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