Package: DistatisR 1.1.1

DistatisR: DiSTATIS Three Way Metric Multidimensional Scaling

Implement DiSTATIS and CovSTATIS (three-way multidimensional scaling). DiSTATIS and CovSTATIS are used to analyze multiple distance/covariance matrices collected on the same set of observations. These methods are based on Abdi, H., Williams, L.J., Valentin, D., & Bennani-Dosse, M. (2012) <doi:10.1002/wics.198>.

Authors:Derek Beaton [aut, com, ctb], Herve Abdi [aut, cre]

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DistatisR.pdf |DistatisR.html✨
DistatisR/json (API)

# Install 'DistatisR' in R:
install.packages('DistatisR', repos = c('https://herveabdi.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/herveabdi/distatisr/issues

Datasets:
  • BeersProjectiveMapping - 7 (fictitious) assessors sort and verbally describe 7 Beers using _Projective Mapping_.
  • DistAlgo - Four computer algorithms evaluate the similarity of six faces for distatis analysis
  • Sort - Ten Assessors sorted eight beers for 'distatis' analysis
  • SortSpice - 21 French assessors sorted 16 blends of Spice for 'distatis' analysis
  • amariSorting - 25 assessors twice sort and describe 12 amaris
  • beersBlindSorting - Novices and Experts sorted 3 types of beers from 3 different brewers without and without seeing the beers.
  • multiculturalSortingSpices - 62 assessors from 5 countries sort 16 spice samples
  • sortingWines - Novices and wines experts sort red, rosé, and white wines

On CRAN:

3-way-mdsdistatismetric-multidimensional-scaling

36 exports 4 stars 1.54 score 71 dependencies 1 mentions 40 scripts 371 downloads

Last updated 10 months agofrom:029f5ff9f1. Checks:OK: 1 NOTE: 6. Indexed: yes.

TargetResultDate
Doc / VignettesOKSep 05 2024
R-4.5-winNOTESep 05 2024
R-4.5-linuxNOTESep 05 2024
R-4.4-winNOTESep 05 2024
R-4.4-macNOTESep 05 2024
R-4.3-winNOTESep 05 2024
R-4.3-macNOTESep 05 2024

Exports:BootFactorScoresBootFromCompromiseChi2DistChi2DistanceFromSortcomputePartial4GroupsComputeSplusCP2MFAnormedCPCP2NuclearNormedCPCP2SUMPCAnormedCPcreateCubeOfCovDisDblCenterDistDist2CPDistanceFromRankDistanceFromSortdistatisGetCmatGetRectCmatGraphDistatisAllGraphDistatisBootGraphDistatisCompromiseGraphDistatisPartialGraphDistatisRvldiaglist2CubeOfCovDisMFAnormCPmmdsNuclearNormedCPprojectVocprojMap2Cuberdiagread.df.excelrvscale1SUMPCAnormCPsupplementalProjection4distatisvocabulary2CT

Dependencies:abindbackportsbootbroomcarcarDatacellrangerclicolorspacecowplotcpp11crayonDerivdoBydplyrfansifarvergenericsggplot2gluegtablehmsisobandjaneaustenrlabelinglatticelifecyclelme4magrittrMASSMatrixMatrixModelsmgcvmicrobenchmarkminqamodelrmunsellnlmenloptrnnetnumDerivpbkrtestpillarpkgconfigprettyGraphsprettyunitsprogresspurrrquantregR6RColorBrewerRcppRcppEigenreadxlrematchrlangscalesSnowballCSparseMstringistringrsurvivaltibbletidyrtidyselecttidytexttokenizersutf8vctrsviridisLitewithr

Readme and manuals

Help Manual

Help pageTopics
implements three way metric multidimensional scaling: DISTATIS and COVSTATIS.DistatisR-package DiSTATISR DistatisR
25 assessors twice sort and describe 12 amaris (i.e., bitter)amariSorting
Novices and Experts sorted 3 types of beers from 3 different brewers without and without seeing the beers.beersBlindSorting
An example of an excel file storing the Flash Profile of 6 (fictitious) assessors evaluating 7 (imaginary) beers. This excel file can be read by 'read.df.excel'.BeersFlashProfile
7 (fictitious) assessors sort and verbally describe 7 Beers using _Projective Mapping_.BeersProjectiveMapping BeersProjectiveNapping
An example of an excel file with Projective Mapping data and vocabulary. This excel file can be read by 'read.df.excel'.BeersProjectiveMapping_xlsx BeersProjectiveNapping_xlsx
Computes observation factor scores Bootstrap replicates from partial factor scores.BootFactorScores
'BootFromCompromise': Computes Bootstrap replicates of the (observation) factor scores by creating bootstrapped compromises.BootFromCompromise
Computes the chi2 distance between the rows of a rectangular matrix (with positive elements).Chi2Dist
'Chi2DistanceFromSort': Creates a 3-dimensional chi2 distance array from the results of a sorting task.Chi2DistanceFromSort
Computes group alphas and group factor scores for K groups of observations in 'distatis'.computePartial4Groups
ComputeSplusComputeSplus
CP2MFAnormedCPCP2MFAnormedCP
CP2NuclearNormedCPCP2NuclearNormedCP
CP2SUMPCAnormedCPCP2SUMPCAnormedCP
compute a cube of covariance and a cube of distance between the items (rows) of a brick of measurements (when all blocks have the same number of variables).createCubeOfCovDis
Double Center a distance matrixDblCenterDist
Dist2CPDist2CP
Four computer algorithms evaluate the similarity of six faces for distatis analysisDistAlgo
'DistanceFromRank': Creates a 3-dimensional distance array from the results of a ranking task.DistanceFromRank
Creates a 3-dimensional distance array from the results of a sorting task.DistanceFromSort
3-Way MDS based on the "STATIS" optimization procedure.CovSTATIS covstatis DiSTATIS distatis
GetCmatGetCmat
GetRectCmatGetRectCmat
This function combines the functionality of 'GraphDistatisCompromise', 'GraphDistatisPartial', 'GraphDistatisBoot', and 'GraphDistatisRv'.GraphDistatisAll
'GraphDistatisBoot' Plot maps of the factor scores of the observations and their bootstrapped confidence intervals (as confidence ellipsoids or peeled hulls) for a DISTATIS analysis.GraphDistatisBoot
Plot maps of the factor scores of the observations for a DISTATIS analysisGraphDistatisCompromise
Plot maps of the factor scores and partial factor scores of the observations for a DISTATIS analysis.GraphDistatisPartial
Plot maps of the factor scores (from the Rv matrix) of the distance matrices for a DISTATIS analysisGraphDistatisRv
compute a cube of covariance and a cube of distance between the items (rows) of a matrix of measurements comprising K different blocks of possibly different number of variables.list2CubeOfCovDis
MFAnormCPMFAnormCP
Metric (classical) Multidimensional Scaling (a.k.a Principal Coordinate Analysis) of a (squared Euclidean) Distance Matrix.mmds
62 assessors from 5 countries sort 16 spice samplesmulticulturalSortingSpices
NuclearNormedCPNuclearNormedCP
'OrangeJuiceSortingRawData': an example of an excel file with Sorting data and vocabulary. This excel file can be read by 'read.df.excel'.OrangeJuiceSortingRawData
Compute barycentric projections for count-like description of the items of a 'distatis'-type of analysis.projectVoc
\ reshape a data matrix from projective mapping into a brick of data for a 'distatis' analysis.projMap2Cube
'read.df.excel' reads 'distatis' formated ranking or sorting data from an excel file.read.df.excel
Function to compute the RV coefficient between to conformable matricesrv
A variation over the base 'R' scale function that avoids the "divide by 0 = NA" problem.scale1
Ten Assessors sorted eight beers for 'distatis' analysisSort SortingBeer
21 French assessors sorted 16 blends of Spice for 'distatis' analysisSortingSpice SortSpice
Novices and wines experts sort red, rosé, and white winessortingWines
SUMPCAnormCPSUMPCAnormCP
Supplementary element(s) projection in DISTATISsupplementalProjection4distatis
Transforms a data.frame of products by vocabulary of assessors into a products by words (from vocabulary) contingency table.vocabulary2CT
'WinesRankingRawData': an example of an excel file with (simulated) ranking data. Can be read with the function 'read.df.excel()'.WinesRankingRawData