R Development Page

Contributed R Packages

Below is a list of all packages provided by project STOPS.

Important note for package binaries: R-Forge provides these binaries only for the most recent version of R, but not for older versions. In order to successfully install the packages provided on R-Forge, you have to switch to the most recent version of R or, alternatively, install from the package sources (.tar.gz).

Packages

cops	Cluster Optimized Proximity Scaling
	Multidimensional scaling (MDS) methods that aim at pronouncing the clustered appearance of the configuration (Rusch, Mair & Hornik, 2021, ). They achieve this by transforming proximities/distances with explicit power functions and penalizing the fitting criterion with a clusteredness index, the OPTICS Cordillera (Rusch, Hornik & Mair, 2018, ). There are two variants: One for finding the configuration directly (COPS-C) with given explicit power transformations and implicit ratio, interval and nonmetric optimal scaling transformations (Borg & Groenen, 2005, ISBN:978-0-387-28981-6), and one for using the augmented fitting criterion to find optimal hyperparameters for the explicit transformations (P-COPS). The package contains various functions, wrappers, methods and classes for fitting, plotting and displaying a large number of different MDS models (most of the functionality in smacofx) in the COPS framework. The package further contains a function for pattern search optimization, the ``Adaptive Luus-Jaakola Algorithm (Rusch, Mair & Hornik, 2021,) and a functions to calculate the phi-distances for count data or histograms.
	Version: 1.11-1 | Last change: 2024-03-15 18:34:43+01 | Rev.: 500
	Download: (.tar.gz) | (.zip) | Build status: Current | Stable Release: Get cops 1.3-1 from CRAN
	R install command: install.packages("cops", repos="http://R-Forge.R-project.org")
	Logs:   Package build: Source package (Linux x86_64) Windows binary (x86_64/i386) Package check: Linux x86_64 (patched) | Linux x86_64 (devel) Windows (patched) | Windows (devel)

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cordillera	Calculation of the OPTICS Cordillera
	Functions for calculating the OPTICS Cordillera. The OPTICS Cordillera measures the amount of clusteredness in a numeric data matrix within a distance-density based framework for a given minimum number of points comprising a cluster, as described in Rusch, Hornik, Mair (2018) . We provide an R native version with methods for printing, summarizing, and plotting the result.
	Version: 1.0-2 | Last change: 2023-04-19 12:16:56+02 | Rev.: 385
	Download: (.tar.gz) | (.zip) | Build status: Current | Stable Release: Get cordillera 1.0-0 from CRAN
	R install command: install.packages("cordillera", repos="http://R-Forge.R-project.org")
	Logs:   Package build: Source package (Linux x86_64) Windows binary (x86_64/i386) Package check: Linux x86_64 (patched) | Linux x86_64 (devel) Windows (patched) | Windows (devel)

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smacofx	Flexible Multidimensional Scaling and smacof Extensions
	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, ) with ratio and interval optimal scaling, Multiscale MDS (Ramsay, 1977, ) with ratio and interval optimal scaling, S-stress MDS (ALSCAL; Takane, Young & De Leeuw, 1977, ) with ratio and interval optimal scaling, elastic scaling (McGee, 1966, ) with ratio and interval optimal scaling, r-stress MDS (De Leeuw, Groenen & Mair, 2016, ) with ratio, interval and non-metric optimal scaling, power-stress MDS (POST-MDS; Buja & Swayne, 2002 ) with ratio and interval optimal scaling, restricted power-stress (Rusch, Mair & Hornik, 2021, ) with ratio and interval optimal scaling, approximate power-stress with ratio optimal scaling (Rusch, Mair & Hornik, 2021, ), Box-Cox MDS (Chen & Buja, 2013, ), local MDS (Chen & Buja, 2009, ), curvilinear component analysis (Demartines & Herault, 1997, ) and curvilinear distance analysis (Lee, Lendasse & Verleysen, 2004, ). 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 dissimiliarity matrices).
	Version: 1.5-0 | Last change: 2024-03-15 18:34:43+01 | Rev.: 500
	Download: (.tar.gz) | (.zip) | Build status: Current | Stable Release: Get smacofx 0.6-6 from CRAN
	R install command: install.packages("smacofx", repos="http://R-Forge.R-project.org")
	Logs:   Package build: Source package (Linux x86_64) Windows binary (x86_64/i386) Package check: Linux x86_64 (patched) | Linux x86_64 (devel) Windows (patched) | Windows (devel)

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stops	Structure Optimized Proximity Scaling
	Methods that use flexible variants of multidimensional scaling (MDS) which incorporate parametric nonlinear distance transformations and trade-off the goodnes-of-fit fit with structure considerations to find optimal hyperparameters, also known as structure optimized proximity scaling (STOPS) (Rusch, Mair & Hornik, 2023,). The package contains various functions, wrappers, methods and classes for fitting, plotting and displaying different 1-way MDS models with ratio, interval, ordinal optimal scaling in a STOPS framework. These cover essentially the functionality of the package smacofx, including Torgerson (classical) scaling with power transformations of dissmiliarities, SMACOF MDS with powers of dissmiliarities, Sammon mapping with powers of dissmiliarities, elastic scaling with powers of dissmiliarities, spherical SMACOF with powers of dissmiliarities, (ALSCAL) s-stress MDS with powers of dissmiliarities, r-stress MDS, MDS with powers of dissmiliarities and configuration distances, elastic scaling powers of dissmiliarities and configuration distances, Sammon mapping powers of dissmiliarities and configuration distances, power stress MDS (POST-MDS), approximate power stress, Box-Cox MDS, local MDS, Isomap, curvilinear component analysis (CLCA), curvilinear distance analysis (CLDA) and sparsified (power) multidimensional scaling and (power) multidimensional distance analysis (experimental models from smacofx influenced by CLCA). All of these models can also be fit by optimizing over hyperparameters based on godness-of-fit fit only (i.e., no structure considerations). The package further contains functions for optimization, specifically the adaptive Luus-Jaakola algorithm and a wrapper for Bayesian optimization with treed Gaussian process with jumps to linear models, and functions for various c-structuredness indices.
	Version: 1.5-1 | Last change: 2024-03-15 18:34:43+01 | Rev.: 500
	Download: (.tar.gz) | (.zip) | Build status: Current | Stable Release: Get stops 1.0-1 from CRAN
	R install command: install.packages("stops", repos="http://R-Forge.R-project.org")
	Logs:   Package build: Source package (Linux x86_64) Windows binary (x86_64/i386) Package check: Linux x86_64 (patched) | Linux x86_64 (devel) Windows (patched) | Windows (devel)

 

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