psvmSDR: Unified Principal Sufficient Dimension Reduction Package

A unified and user-friendly framework for applying the principal sufficient dimension reduction methods for both linear and nonlinear cases. The package has an extendable power by varying loss functions for the support vector machine, even for an user-defined arbitrary function, unless those are convex and differentiable everywhere over the support (Li et al. (2011) <doi:10.1214/11-AOS932>). Also, it provides a real-time sufficient dimension reduction update procedure using the principal least squares support vector machine (Artemiou et al. (2021) <doi:10.1016/j.patcog.2020.107768>).

Version:	1.0.1
Imports:	stats, graphics
Suggests:	testthat
Published:	2024-08-30
DOI:	10.32614/CRAN.package.psvmSDR
Author:	Jungmin Shin [aut, cre], Seung Jun Shin [aut], Andreas Artemiou [aut]
Maintainer:	Jungmin Shin <jungminshin at korea.ac.kr>
License:	GPL-2
NeedsCompilation:	no
Materials:	README
CRAN checks:	psvmSDR results

Documentation:

Reference manual:

psvmSDR.pdf

Downloads:

Package source:	psvmSDR_1.0.1.tar.gz
Windows binaries:	r-devel: psvmSDR_1.0.1.zip, r-release: psvmSDR_1.0.1.zip, r-oldrel: psvmSDR_1.0.1.zip
macOS binaries:	r-release (arm64): psvmSDR_1.0.1.tgz, r-oldrel (arm64): psvmSDR_1.0.1.tgz, r-release (x86_64): psvmSDR_1.0.1.tgz, r-oldrel (x86_64): psvmSDR_1.0.1.tgz

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