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:	0.2-0
Depends:	R (≥ 3.5.0), Matrix
Imports:	methods, stats
Published:	2024-08-19
Author:	Xin-Yee Lam [aut, cre], J.S. Marron [aut], Defeng Sun [aut], Kim-Chuan Toh [aut]
Maintainer:	Xin-Yee Lam <matlxy at nus.edu.sg>
License:	GPL-2
URL:	https://arxiv.org/pdf/1604.05473
NeedsCompilation:	no
CRAN checks:	DWDLargeR results

Documentation:

Reference manual:

DWDLargeR.html , DWDLargeR.pdf

Downloads:

Package source:	DWDLargeR_0.2-0.tar.gz
Windows binaries:	r-devel: DWDLargeR_0.2-0.zip, r-release: DWDLargeR_0.2-0.zip, r-oldrel: DWDLargeR_0.2-0.zip
macOS binaries:	r-release (arm64): DWDLargeR_0.2-0.tgz, r-oldrel (arm64): DWDLargeR_0.2-0.tgz, r-release (x86_64): DWDLargeR_0.2-0.tgz, r-oldrel (x86_64): DWDLargeR_0.2-0.tgz
Old sources:	DWDLargeR archive

Reverse dependencies:

Reverse suggests:

DataSimilarity

Linking:

Please use the canonical form https://CRAN.R-project.org/package=DWDLargeR to link to this page.