Cluster Optimized Proximity Scaling
Overview
Multidimensional scaling (MDS) methods that aim at pronouncing the clustered appearance of the configuration (Rusch, Mair & Hornik, 2021, doi:10.1080/10618600.2020.1869027). 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, doi:10.1080/10618600.2017.1349664). There are two variants: One for finding the configuration directly (COPS-C) with given explicit power transformations and implicit ratio, interval and non-metric 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,doi:10.1080/10618600.2020.1869027) and a functions to calculate the phi-distances for count data or histograms.
- Fixed bug in optimal scaling of disparities.
From NEWS in the release
Install
Health
- OK13 OK2026-09-04
- NOTE12 OK, 1 NOTE2026-08-31
- OK13 OK2026-08-05
- NOTE12 OK, 1 NOTE2026-08-01
- OK13 OK2026-06-09
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- ERROR12 OK, 1 ERROR2026-06-08
- OK13 OK2026-05-02
- ERROR11 OK, 1 ERROR2026-04-25
- OK14 OK2026-04-10
- ERROR13 OK, 1 ERROR2026-04-09
- OK14 OK2026-03-10
Documentation
- Help pages
- 39 (1 internal)includes a package overview page
- Examples that run
- 90%9 run in a plain check · 1 only when donttest examples are enabled (R CMD check --as-cran)
- Exported functions with examples
- 80%
- Documented parameters
- 87%
- Return-value docs
- 100%
- Help pages citing references
- 0%
Downloads
Repository
Repository r-forge.r-project.org/projects/stops is linked, but repository-practices checks have not run for it yet. Checks are GitHub-only for now.
Dependencies
Installing cops adds 161 packages (88 with compiled code, 114 MB of source tarballs). Heaviest: stringi 11 MB, ggplot2 6.0 MB, data.table 5.7 MB.
Code & Tests
Datasets
People & History
Pick two releases to compare their code metrics.
- RR 4.6.0 released · 2026-04-24
- RR 4.5.0 released · 2025-04-11
- 1.12-1Latest
- 1.11-32024-06-27 · diff ↗ ·
removed 7 exports
cmdscale, conf_adjust, plot3dstatic, powerStressFast, powerStressMin, sammon, torgersonadded 3 exports
copStressMin, copsc, phidistance - RR 4.4.0 released · 2024-04-24
- RR 4.3.0 released · 2023-04-21
- 1.3-12023-01-19 · diff ↗
- RR 4.2.0 released · 2022-04-22
- RR 4.1.0 released · 2021-05-18
- 1.2-02021-03-23 · diff ↗
- RR 4.0.0 released · 2020-04-24
- 1.0-22019-11-01
- RR 3.6.0 released · 2019-04-26
Package metadata
- First published
- 2019-11-01
- Total releases
- 5 / 7 yrs
- License
- GPL-2 | GPL-3 OSI
- Minimum R
- ≥ 3.5.0
- Bundled data
- 13 KB / 2 files
- Download size
- 464 KB
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Run in R for the authors' preferred citation:
citation("cops")The package provides a citation file that builds its entry when R runs it. Run citation() to see it.
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