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1.9-1

Structure Optimized Proximity Scaling

0packages depend
4.6Kdownloads / year
test coverage
13/13checks pass

Overview

About
Maintained by Thomas RuschFirst published 2023-01-204 releasesCRAN page ↗

Methods that use flexible variants of multidimensional scaling (MDS) which incorporate parametric nonlinear distance transformations and trade-off the goodness-of-fit fit with structure considerations to find optimal hyperparameters, also known as structure optimized proximity scaling (STOPS) (Rusch, Mair & Hornik, 2023,doi:10.1007/s11222-022-10197-w). 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 dissimilarities, SMACOF MDS with powers of dissimilarities, Sammon mapping with powers of dissimilarities, elastic scaling with powers of dissimilarities, spherical SMACOF with powers of dissimilarities, (ALSCAL) s-stress MDS with powers of dissimilarities, r-stress MDS, MDS with powers of dissimilarities and configuration distances, elastic scaling powers of dissimilarities and configuration distances, Sammon mapping powers of dissimilarities 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 goodness-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. Hyperparameter optimization can be done with a number of techniques but we recommend either Bayesian optimization or particle swarm. For using "Kriging", users need to install a version of the archived 'DiceOptim' R package.

Install

Health

CRAN checks
13OK
Slowest check: 5.8 min · r-devel-linux-x86_64-fedora-clang
Code health
None
Tests · ratio 0.00
not tracked
Coverage
100%
Documentation · exports
16
Dependencies · direct
Check history
  • OK2026-06-09
    13 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
  • ERROR2026-06-08
    12 OK · 0 NOTE · 0 WARNING · 1 ERROR · 0 FAILURE
  • NOTE2026-06-07
    12 OK · 1 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
  • OK2026-05-02
    13 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
  • ERROR2026-04-25
    11 OK · 0 NOTE · 0 WARNING · 1 ERROR · 0 FAILURE
Show 5 earlier snapshots
  • OK2026-04-10
    14 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
  • ERROR2026-04-09
    13 OK · 0 NOTE · 0 WARNING · 1 ERROR · 0 FAILURE
  • OK2026-04-06
    14 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
  • ERROR2026-04-04
    13 OK · 0 NOTE · 0 WARNING · 1 ERROR · 0 FAILURE
  • OK2026-03-10
    14 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE

Documentation

Documentation
READMENoVignettesYes · dynamicpkgdown siteNoNEWSYes · 100% structuredCode of conductNoContributing guideNo
Examples that run
96%
Documented parameters
91%
Return-value docs
100%
References docs
0%

Downloads

4.6K
CRAN downloads in the past year
Rank #10,966 · ~13/day · ~383/mo
Daily download trend is not available in this view yet.
24830 days
97790 days
4.6K1 year
Compare downloads with other packages →
Also on92 r2u41 c2d4u

Repository

Repository practices

Upstream repositoryBeta

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.

How this is detected·Detection ruleset v1 (2026-07-18)

Dependencies

Declared dependencies
19 external dependencies (excludes base and recommended)
Depends (2)
R >= 3.5.0smacofx
LinkingTo (0)
none
Enhances (0)
none
Reverse dependencies
0direct
0indirect

Nothing depends on this yet.

Code & Tests

Code Composition
Rd 3,702 (43%)R 3,615 (42%)Vignettes 1,305 (15%)Other 2 (0%)
Code characteristics
Object systems
S39
Cyclomatic complexity
5.0 median / 53 max

Test coverage

Line coverage

Expression

Tests / Examples

Functions

63 48 exported

Complexity

4.9 avg / 53 max

Call network

63 nodes / 33 edges

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Lowest coverage

Per-function coverage is not measured for this package yet.

Datasets

Bundled datasets · 2
NameClassRows × ColsAlso ships in
Pendigits500data.frame500 × 17
Swissrolldata.frame150 × 4

People & History

People (3)
Maintainer (1)
Author, Maintainer
Authors (2)
Author, Maintainer
Contributors (1)
Contributor
Listed in earlier versions (2)
no longer listed · 1.0-1
no longer listed · 1.0-1
Package Timeline

4 releases. Pick two to compare their code metrics. R releases are shown for context.

  • R
    R 4.6.0 released · 2026-04-24
  • 1.9-1Latest
    2025-04-28 · current release · diff ↗
  • R
    R 4.5.0 released · 2025-04-11
  • 1.8-2
    2024-09-22 · diff ↗
  • 1.6-2
    2024-06-28 · diff ↗
  • R
    R 4.4.0 released · 2024-04-24
  • R
    R 4.3.0 released · 2023-04-21
  • 1.0-1
    2023-01-20
  • R
    R 4.2.0 released · 2022-04-22

Package metadata

First published
2023-01-20
Total releases
4 / 3 yrs
License
GPL-2 | GPL-3 OSI
Minimum R
≥ 3.5.0
Bundled data
20 KB / 3 files
Download size
451 KB
Installed size
not tracked yet
With dependencies
not tracked yet
Appears in task views
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