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optiscale  

Optimal Scaling
View on CRAN: Click here


Download and install optiscale package within the R console
Install from CRAN:
install.packages("optiscale")

Install from Github:
library("remotes")
install_github("cran/optiscale")

Install by package version:
library("remotes")
install_version("optiscale", "1.2.3")



Attach the package and use:
library("optiscale")
Maintained by
Dave Armstrong
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2014-08-01
Latest Update: 2024-05-16
Description:
Optimal scaling of a data vector, relative to a set of targets, is obtained through a least-squares transformation subject to appropriate measurement constraints. The targets are usually predicted values from a statistical model. If the data are nominal level, then the transformation must be identity-preserving. If the data are ordinal level, then the transformation must be monotonic. If the data are discrete, then tied data values must remain tied in the optimal transformation. If the data are continuous, then tied data values can be untied in the optimal transformation.
How to cite:
Dave Armstrong (2014). optiscale: Optimal Scaling. R package version 1.2.3, https://cran.r-project.org/web/packages/optiscale. Accessed 05 Jun. 2026.
Previous versions and publish date:
1.1 (2014-08-01 07:55), 1.2.2 (2021-02-03 06:40), 1.2 (2020-02-28 08:20)
Other packages that cited optiscale R package
View optiscale citation profile
Other R packages that optiscale depends, imports, suggests or enhances
Complete documentation for optiscale
Functions, R codes and Examples using the optiscale R package
Some associated functions: elec92 . methods . opscale . optiscale-package . os.plot . shepard . stress . 
Some associated R codes: opscalev16.R .  Full optiscale package functions and examples
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