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lmds: Landmark Multi-Dimensional Scaling

A fast dimensionality reduction method scaleable to large numbers of samples. Landmark Multi-Dimensional Scaling (LMDS) is an extension of classical Torgerson MDS, but rather than calculating a complete distance matrix between all pairs of samples, only the distances between a set of landmarks and the samples are calculated.

Version:0.1.0
Imports:assertthat,dynutils (≥ 1.0.3),irlba,Matrix
Suggests:testthat
Published:2019-09-27
DOI:10.32614/CRAN.package.lmds
Author:Robrecht CannoodtORCID iD [aut, cre] (github: rcannood), Wouter SaelensORCID iD [aut] (github: zouter)
Maintainer:Robrecht Cannoodt <rcannood at gmail.com>
BugReports:https://github.com/dynverse/lmds/issues
License:GPL-3
URL:http://github.com/dynverse/lmds
NeedsCompilation:no
Materials:README,NEWS
CRAN checks:lmds results

Documentation:

Reference manual:lmds.html ,lmds.pdf

Downloads:

Package source: lmds_0.1.0.tar.gz
Windows binaries: r-devel:lmds_0.1.0.zip, r-release:lmds_0.1.0.zip, r-oldrel:lmds_0.1.0.zip
macOS binaries: r-release (arm64):lmds_0.1.0.tgz, r-oldrel (arm64):lmds_0.1.0.tgz, r-release (x86_64):lmds_0.1.0.tgz, r-oldrel (x86_64):lmds_0.1.0.tgz

Reverse dependencies:

Reverse imports:dyndimred,dyngen,SCORPIUS

Linking:

Please use the canonical formhttps://CRAN.R-project.org/package=lmdsto link to this page.


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