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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

  Cluster optimized proximity scaling (COPS) refers to multidimensional scaling methods that aim at pronouncing the clustered appearance of the configuration. They achieve this by transforming proximities/distances with power functions and augment the fitting criterion with a clusteredness index, the OPTICS Cordillera. There are two variants: One for finding the configuration directly for given parameters (COPS-C) for ratio, interval and nonmetric MDS, and one for using the augmented fitting criterion to find optimal parameters (P-COPS). The package contains various functions, wrappers, methods and classes for fitting, plotting and displaying different MDS models in a COPS framework like ratio, interval and nometric MDS for COPS-C and P-COPS with Torgerson scaling, SMACOF, Sammon mapping, elastic scaling, symmetric SMACOF, spherical SMACOF, sstress, rstress, powermds, power elastic scaling, power sammon mapping, powerstress and approximated power stress. All of these models can also solely be fit as MDS with power transformations. The package further contains a function for pattern search optimization (Adaptive LJ Algorithm).
  Version: 0.7-0 | Last change: 2018-08-13 00:26:22+02 | Rev.: 270
  Download: linux(.tar.gz) | windows(.zip) | Build status: Current
  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)


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) . There is an R native version and a version that uses ELKI, with methods for printing, summarizing, and plotting the result. There also is an interface to the reference implementation of OPTICS in ELKI.
  Version: 0.8-1 | Last change: 2018-08-06 21:46:12+02 | Rev.: 266
  Download: linux(.tar.gz) | windows(.zip) | Build status: Current | Stable Release: Get cordillera 0.8-0 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)


stops

STructure Optimized Proximity Scaling

  Structure optimized proximity scaling (STOPS) refers to a collection of methods that fit nonlinear distance transformations in multidimensional scaling (MDS) and trade-off the fit with structure considerations to find optimal parameters or optimal configurations. The package contains various functions, wrappers, methods and classes for fitting, plotting and displaying different MDS models in a STOPS framework like Torgerson scaling, SMACOF, Sammon mapping, elastic scaling, symmetric SMACOF, spherical SMACOF, sstress, rstress, powermds, power elastic scaling, power sammon mapping, powerstress and Isomap. All of these models can also solely be fit as MDS versions (i.e., no structure considerations) . The package further contains functions for optimization (Adaptive LJ and for Bayesian optimization with treed Gaussian process with jump to linear models) and functions for various structuredness indices.
  Version: 0.0-39 | Last change: 2018-11-05 01:05:44+01 | Rev.: 284
  Download: linux(.tar.gz) | windows(.zip) | Build status: Current
  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)

 

Build status codes

0 - Current: the package is available for download. The corresponding package passed checks on the Linux and Windows platform without ERRORs.
1 - Scheduled for build: the package has been recognized by the build system and provided in the staging area.
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