dualScale: Dual Scaling Analysis of Data

Dual Scaling, developed by Professor Shizuhiko Nishisato (1994, ISBN: 0-9691785-3-6), is a fundamental technique in multivariate analysis used for data scaling and correspondence analysis. Its utility lies in its ability to represent multidimensional data in a lower-dimensional space, making it easier to visualize and understand underlying patterns in complex data. This technique has been implemented to handle various types of data, including Contingency and Frequency data (CF), Multiple-Choice data (MC), Sorting data (SO), Paired-Comparison data (PC), and Rank-Order data (RO), providing users with a powerful tool to explore relationships between variables and observations in various fields, from sociology to ecology, enabling deeper and more efficient analysis of multivariate datasets.

Version: 1.0.0
Depends: R (≥ 3.5.0)
Imports: eba, ff, ggplot2, ggrepel, grid, Matrix, matrixcalc, stats, RColorBrewer, glue, utils
Suggests: testthat (≥ 3.0.0), vdiffr
Published: 2023-11-09
Author: Jose G. Clavel ORCID iD [aut], Shizuiko Nishisato ORCID iD [aut], Roberto de la Banda ORCID iD [aut, cre], Antonio Pita ORCID iD [ctb]
Maintainer: Roberto de la Banda <dualScale at gmail.com>
License: AGPL (≥ 3)
NeedsCompilation: no
Citation: dualScale citation info
Materials: README NEWS
CRAN checks: dualScale results

Documentation:

Reference manual: dualScale.pdf

Downloads:

Package source: dualScale_1.0.0.tar.gz
Windows binaries: r-devel: dualScale_1.0.0.zip, r-release: dualScale_1.0.0.zip, r-oldrel: dualScale_1.0.0.zip
macOS binaries: r-release (arm64): dualScale_1.0.0.tgz, r-oldrel (arm64): dualScale_1.0.0.tgz, r-release (x86_64): dualScale_1.0.0.tgz
Old sources: dualScale archive

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