fmds: Multidimensional Scaling Development Kit

Multidimensional scaling (MDS) functions for various tasks that are beyond the beta stage and way past the alpha stage. Currently, options are available for weights, restrictions, classical scaling or principal coordinate analysis, transformations (linear, power, Box-Cox, spline, ordinal), outlier mitigation (rdop), out-of-sample estimation (predict), negative dissimilarities, fast and faster executions with low memory footprints, penalized restrictions, cross-validation-based penalty selection, supplementary variable estimation (explain), additive constant estimation, mixed measurement level distance calculation, restricted classical scaling, etc. More will come in the future. References. Busing (2024) "A Simple Population Size Estimator for Local Minima Applied to Multidimensional Scaling". Manuscript submitted for publication. Busing (2025) "Node Localization by Multidimensional Scaling with Iterative Majorization". Manuscript submitted for publication. Busing (2025) "Faster Multidimensional Scaling". Manuscript in preparation. Barroso and Busing (2025) "e-RDOP, Relative Density-Based Outlier Probabilities, Extended to Proximity Mapping". Manuscript submitted for publication.

Version:	0.1.5
Depends:	R (≥ 3.5.0)
Imports:	graphics, stats
Suggests:	ggplot2, microbenchmark
Published:	2025-06-03
DOI:	10.32614/CRAN.package.fmds
Author:	Frank M.T.A. Busing [aut, cre], Juan Claramunt Gonzalez [aut, com]
Maintainer:	Frank M.T.A. Busing <busing at fsw.leidenuniv.nl>
License:	BSD_2_clause + file LICENSE
NeedsCompilation:	yes
CRAN checks:	fmds results

Documentation:

Downloads:

Linking:

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