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]

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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'))

Peer review:

Datasets:

On CRAN:

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

6 exports 0.09 score 202 dependencies 19 scripts 435 downloads

Last updated 10 months agofrom:de42c22afc. Checks:ERROR: 1 NOTE: 2 OK: 4. Indexed: yes.

TargetResultDate
Doc / VignettesFAILAug 28 2024
R-4.5-winNOTEAug 28 2024
R-4.5-linuxNOTEAug 28 2024
R-4.4-winOKAug 28 2024
R-4.4-macOKAug 28 2024
R-4.3-winOKAug 28 2024
R-4.3-macOKAug 28 2024

Exports:drawIsoquantsfindOptimalSmacofSymoptSmacofSym_mMDSoptSmacofSym_nMDSoptSmacofSymIntervalrotation2dAnimation

Dependencies:abindade4animationaskpassbackportsbase64encbitbit64blobbootbroombslibcachemcandisccarcarDatacheckmatechronclassclassIntclicliprclusterclusterSimcodetoolscolorspacecowplotcpp11crayoncrosstalkcurldata.tableDBIdeldirDerivdigestdoBydoParalleldplyrDTe1071ellipseemmeansestimabilityevaluateFactoMineRfansifarverfastmapflashClustfontawesomeforcatsforeachforeignFormulafsgbmgdatagenericsggplot2ggpolypathggrepelglmnetgluegridExtragsubfngtablegtoolshavenheplotsherehighrHmischmshtmlTablehtmltoolshtmlwidgetshttpuvhttrigraphisobanditeratorsjomojquerylibjsonliteKernSmoothkknnknitrlabelinglaterlatticelazyevalleapslifecyclelme4magickmagrittrMASSMatrixMatrixModelsmemoisemgcvmicemicrobenchmarkmimeminpack.lmminqamitmlmodelrmultcompViewmunsellmvtnormneuralnetnlmenloptrnnetnnlsnumDerivopensslordinalpanpbkrtestpillarpixmappkgconfigplogrplotlyplotrixplyrpngpolynomprettyunitsprincurveprogresspromisesprotoproxypurrrquantregR6randomcoloRrandomForestrappdirsRColorBrewerRcppRcppArmadilloRcppEigenRcppTOMLreadrreshapereticulaterglRJSONIOrlangrmarkdownrpartrprojrootRSDARSpectraRSQLiterstudioapiRtsnes2sassscalesscatterplot3dsfshapeshapessmacofspSparseMspDataspdepsqldfstringistringrsurvivalsymbolicDAsystibbletidyrtidyselecttinytextzdbucminfumapunitsutf8V8vctrsviridisviridisLitevroomweightswithrwkwordcloudxfunXMLxtableyaml

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 Aug 28 2024.

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