# -------------------------------------------- # CITATION file created with {cffr} R package # See also: https://docs.ropensci.org/cffr/ # -------------------------------------------- cff-version: 1.2.0 message: 'To cite package "stops" in publications use:' type: software license: - GPL-2.0-only - GPL-3.0-only title: 'stops: Structure Optimized Proximity Scaling' version: 1.8-2 identifiers: - type: doi value: 10.32614/CRAN.package.stops abstract: 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,). 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. authors: - family-names: Rusch given-names: Thomas email: thomas.rusch@wu.ac.at orcid: https://orcid.org/0000-0002-7773-2096 - family-names: Mair given-names: Patrick orcid: https://orcid.org/0000-0003-0100-6511 preferred-citation: type: manual title: 'stops: Structure Optimized Proximity Scaling' authors: - family-names: Rusch given-names: Thomas email: thomas.rusch@wu.ac.at orcid: https://orcid.org/0000-0002-7773-2096 - family-names: Mair given-names: Patrick orcid: https://orcid.org/0000-0003-0100-6511 notes: R package version 1.8-2 url: https://r-forge.r-project.org/projects/stops/ repository: https://r-forge.r-universe.dev repository-code: https://r-forge.r-project.org/projects/stops/ commit: 941ff5cce826c1b404801f172cd0e72f51e3133e url: https://r-forge.r-project.org/projects/stops/ contact: - family-names: Rusch given-names: Thomas email: thomas.rusch@wu.ac.at orcid: https://orcid.org/0000-0002-7773-2096 references: - type: article title: Structure-based hyperparameter selection with Bayesian optimization in multidimensional scaling authors: - family-names: Rusch given-names: Thomas email: thomas.rusch@wu.ac.at orcid: https://orcid.org/0000-0002-7773-2096 - family-names: Mair given-names: Patrick email: mair@fas.harvard.edu orcid: https://orcid.org/0000-0003-0100-6511 - family-names: Hornik given-names: Kurt email: Kurt.Hornik@R-project.org orcid: https://orcid.org/0000-0003-4198-9911 journal: Statistics and Computing year: '2023' volume: '33' issue: '28' doi: 10.1007/s11222-022-10197-w start: 1-18 - type: report title: Minimizing rstress using nested majorization authors: - family-names: Leeuw given-names: Jan name-particle: de - family-names: Groenen given-names: Patrick - family-names: Mair given-names: Patrick email: mair@fas.harvard.edu orcid: https://orcid.org/0000-0003-0100-6511 year: '2016' url: https://rpubs.com/deleeuw/142619 institution: name: UCLA - type: article title: Stress functions for nonlinear dimension reduction, proximity analysis, and graph drawing. authors: - family-names: Chen given-names: Lisha - family-names: Buja given-names: Andreas journal: Journal of Machine Learning Research year: '2013' volume: '14' start: 1145-1173 - type: article title: Local multidimensional scaling for nonlinear dimension reduction, graph drawing, and proximity analysis. authors: - family-names: Chen given-names: Lisha - family-names: Buja given-names: Andreas journal: Journal of the American Statistical Association year: '2009' volume: '104' start: 209-219