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fmds
View on CRAN: Click
here
Download and install fmds package within the R console
Install from CRAN:
install.packages("fmds")
Install from Github:
library("remotes")
install_github("cran/fmds") Install by package version:
library("remotes")
install_version("fmds", "0.1.5") Attach the package and use:
library("fmds")
Maintained by
Frank M.T.A. Busing
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2025-05-09
Latest Update: 2025-06-03
Description:
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.
How to cite:
Frank M.T.A. Busing (2025). fmds: Multidimensional Scaling Development Kit. R package version 0.1.5, https://cran.r-project.org/web/packages/fmds. Accessed 03 Jul. 2026.
Previous versions and publish date:
0.1.2 (2025-04-25 14:20)
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