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Flexible multidimensional scaling (MDS) methods and extensions to the package 'smacof'. This package contains various functions, wrappers, methods and classes for fitting, plotting and displaying a large number of different flexible MDS models (some as of yet unpublished). These are: Torgerson scaling (Torgerson, 1958, ISBN:978-0471879459) with powers, Sammon mapping (Sammon, 1969, <doi:10.1109/T-C.1969.222678>) with ratio and interval optimal scaling, Multiscale MDS (Ramsay, 1977, <doi:10.1007/BF02294052>) with ratio and interval optimal scaling, S-stress MDS (ALSCAL; Takane, Young & De Leeuw, 1977, <doi:10.1007/BF02293745>) with ratio and interval optimal scaling, elastic scaling (McGee, 1966, <doi:10.1111/j.2044-8317.1966.tb00367.x>) with ratio and interval optimal scaling, r-stress MDS (De Leeuw, Groenen & Mair, 2016, <https://rpubs.com/deleeuw/142619>) with ratio, interval and non-metric optimal scaling, power-stress MDS (POST-MDS; Buja & Swayne, 2002 <doi:10.1007/s00357-001-0031-0>) with ratio and interval optimal scaling, restricted power-stress (Rusch, Mair & Hornik, 2021, <doi:10.1080/10618600.2020.1869027>) with ratio and interval optimal scaling, approximate power-stress with ratio optimal scaling (Rusch, Mair & Hornik, 2021, <doi:10.1080/10618600.2020.1869027>), Box-Cox MDS (Chen & Buja, 2013, <https://jmlr.org/papers/v14/chen13a.html>), local MDS (Chen & Buja, 2009, <doi:10.1198/jasa.2009.0111>), curvilinear component analysis (Demartines & Herault, 1997, <doi:10.1109/72.554199>) and curvilinear distance analysis (Lee, Lendasse & Verleysen, 2004, <doi:10.1016/j.neucom.2004.01.007>). There also are experimental models (e.g., sparsified MDS and sparsified POST-MDS). Some functions are suitably flexible to allow any other sensible combination of explicit power transformations for weights, distances and input proximities with implicit ratio, interval or non-metric optimal scaling of the input proximities. Most functions use a Majorization-Minimization algorithm. Currently the methods are only available for one-mode data (symmetric dissimilarity matrices).
Version: | 1.6-1 |
Depends: | R (≥ 3.5.0), smacof (≥ 1.10-4) |
Imports: | MASS, minqa, plotrix, ProjectionBasedClustering, weights, vegan |
Published: | 2024-09-22 |
DOI: | 10.32614/CRAN.package.smacofx |
Author: | Thomas Rusch [aut, cre], Jan de Leeuw [aut], Lisha Chen [aut], Patrick Mair [aut] |
Maintainer: | Thomas Rusch <thomas.rusch at wu.ac.at> |
BugReports: | https://r-forge.r-project.org/tracker/?atid=5375&group_id=2037&func=browse |
License: | GPL-2 | GPL-3 |
URL: | https://r-forge.r-project.org/projects/stops/ |
NeedsCompilation: | no |
Materials: | NEWS |
In views: | Psychometrics |
CRAN checks: | smacofx results |
Reference manual: | smacofx.pdf |
Package source: | smacofx_1.6-1.tar.gz |
Windows binaries: | r-devel: smacofx_1.6-1.zip, r-release: smacofx_1.6-1.zip, r-oldrel: smacofx_1.6-1.zip |
macOS binaries: | r-release (arm64): smacofx_1.6-1.tgz, r-oldrel (arm64): smacofx_1.6-1.tgz, r-release (x86_64): smacofx_1.6-1.tgz, r-oldrel (x86_64): smacofx_1.6-1.tgz |
Old sources: | smacofx archive |
Reverse depends: | cops, stops |
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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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