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 |
| Author: | Robrecht Cannoodt 
[aut, cre] (rcannood),
Wouter Saelens
[aut] (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.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, SCORPIUS |
Linking:
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