Package: mdsOpt 0.7-6

mdsOpt: Searching for Optimal MDS Procedure for Metric and Interval-Valued Data

Selecting the optimal multidimensional scaling (MDS) procedure for metric data via metric MDS (ratio, interval, mspline) and nonmetric MDS (ordinal). Selecting the optimal multidimensional scaling (MDS) procedure for interval-valued data via metric MDS (ratio, interval, mspline).Selecting the optimal multidimensional scaling procedure for interval-valued data by varying all combinations of normalization and optimization methods.Selecting the optimal MDS procedure for statistical data referring to the evaluation of tourist attractiveness of Lower Silesian counties. (Borg, I., Groenen, P.J.F., Mair, P. (2013) <doi:10.1007/978-3-642-31848-1>, Walesiak, M. (2016) <doi:10.15611/ekt.2016.2.01>, Walesiak, M. (2017) <doi:10.15611/ekt.2017.3.01>).

Authors:Marek Walesiak [aut], Andrzej Dudek [aut, cre]

mdsOpt_0.7-6.tar.gz
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mdsOpt.pdf |mdsOpt.html✨
mdsOpt/json (API)

# Install 'mdsOpt' in R:
install.packages('mdsOpt', repos = c('https://a-dudek-ue.r-universe.dev', 'https://cloud.r-project.org'))
Datasets:

On CRAN:

Conda:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

2.28 score 19 scripts 308 downloads 6 exports 203 dependencies

Last updated 1 years agofrom:de42c22afc. Checks:1 ERROR, 3 NOTE, 5 OK. Indexed: yes.

TargetResultLatest binary
Doc / VignettesFAILMar 27 2025
R-4.5-winNOTEMar 27 2025
R-4.5-macNOTEMar 27 2025
R-4.5-linuxNOTEMar 27 2025
R-4.4-winOKMar 27 2025
R-4.4-macOKMar 27 2025
R-4.4-linuxOKMar 27 2025
R-4.3-winOKMar 27 2025
R-4.3-macOKMar 27 2025

Exports:drawIsoquantsfindOptimalSmacofSymoptSmacofSym_mMDSoptSmacofSym_nMDSoptSmacofSymIntervalrotation2dAnimation

Dependencies:abindade4animationaskpassbackportsbase64encbitbit64blobbootbroombslibcachemcarcarDatacheckmatechronclassclassIntclicliprclusterclusterSimcodetoolscolorspacecowplotcpp11crayoncrosstalkcurldata.tableDBIdeldirDerivdigestdoBydoParalleldplyrDTe1071ellipseemmeansestimabilityevaluateFactoMineRfansifarverfastmapflashClustfontawesomeforcatsforeachforeignFormulafsgbmgdatagenericsggplot2ggpolypathggrepelglmnetgluegridExtragsubfngtablegtoolshavenherehighrHmischmshtmlTablehtmltoolshtmlwidgetshttpuvhttrigraphisobanditeratorsjomojquerylibjsonliteKernSmoothkknnknitrlabelinglaterlatticelazyevalleapslifecyclelme4magickmagrittrMASSMatrixMatrixModelsmemoisemgcvmicemicrobenchmarkmimeminpack.lmminqamitmlmodelrmultcompViewmunsellmvtnormneuralnetnlmenloptrnnetnnlsnumDerivopensslordinalpanpbkrtestpillarpixmappkgconfigplogrplotlyplotrixplyrpngpolynomprettyunitsprincurveprogresspromisesprotoproxypurrrquantregR6randomcoloRrandomForestrappdirsrbibutilsRColorBrewerRcppRcppArmadilloRcppEigenRcppTOMLRdpackreadrreformulasreshapereticulaterglRJSONIOrlangrmarkdownrpartrprojrootRSDARSpectraRSQLiterstudioapiRtsnes2sassscalesscatterplot3dsfshapeshapessmacofspSparseMspDataspdepsqldfstringistringrsurvivalsymbolicDAsystibbletidyrtidyselecttinytextzdbucminfumapunitsutf8V8vctrsviridisviridisLitevroomweightswithrwkwordcloudxfunXMLxtableyaml

MdsOPT package, published in M. Walesiak and A. Dudek, "Searching for an Optimal MDS Procedure for Metric and Interval-Valued Data using mdsOpt R package", in: Education Excellence and Innovation Management: A 2025 Vision to Sustain Economic Development during Global Challenges, 2020, pp. 307-324.

Rendered frommdsOpt.ltxusingR.rsp::texon Mar 27 2025.

Last update: 2020-07-20
Started: 2019-08-28