Package: DistatisR 1.1.2

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, ctb], Ju-Chi Yu [aut, ctb], Vincent Guillemot [aut, ctb], Herve Abdi [aut, cre]

DistatisR_1.1.2.tar.gz
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manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
DistatisR/json (API)

# Install 'DistatisR' in R:

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

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

Datasets:

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.
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
multiculturalSortingSpices - 62 assessors from 5 countries sort 16 spice samples
Sort - Ten Assessors sorted eight beers for 'distatis' analysis
sortingWines - Novices and wines experts sort red, rosé, and white wines
SortSpice - 21 French assessors sorted 16 blends of Spice for 'distatis' analysis

On CRAN:

3-way-mds distatis metric-multidimensional-scaling

4.47 score 4 stars 49 scripts 361 downloads 1 mentions 36 exports 81 dependencies

Last updated from:88e9004b1b. Checks:9 OK. Indexed: yes.

Target	Result	Time
linux-devel-x86_64	OK	179
source / vignettes	OK	170
linux-release-x86_64	OK	180
macos-release-arm64	OK	146
macos-oldrel-arm64	OK	210
windows-devel	OK	121
windows-release	OK	110
windows-oldrel	OK	115
wasm-release	OK	116

Exports:BootFactorScores BootFromCompromise Chi2Dist Chi2DistanceFromSort computePartial4Groups ComputeSplus CP2MFAnormedCP CP2NuclearNormedCP CP2SUMPCAnormedCP createCubeOfCovDis DblCenterDist Dist2CP DistanceFromRank DistanceFromSort distatis GetCmat GetRectCmat GraphDistatisAll GraphDistatisBoot GraphDistatisCompromise GraphDistatisPartial GraphDistatisRv ldiag list2CubeOfCovDis MFAnormCP mmds NuclearNormedCP projectVoc projMap2Cube rdiag read.df.excel rv scale1 SUMPCAnormCP supplementalProjection4distatis vocabulary2CT

Dependencies:abind backports boot broom car carData cellranger cli colorspace cowplot cpp11 crayon Deriv doBy dplyr farver forecast Formula fracdiff generics ggplot2 glue gtable hms isoband janeaustenr labeling lattice lifecycle lme4 lmtest magrittr MASS Matrix MatrixModels mgcv microbenchmark minqa modelr nlme nloptr nnet numDeriv pbkrtest pillar pkgconfig prettyGraphs prettyunits progress purrr quantreg R6 rbibutils RColorBrewer Rcpp RcppArmadillo RcppEigen Rdpack readxl reformulas rematch rlang S7 scales SnowballC SparseM stringi stringr survival tibble tidyr tidyselect tidytext timeDate tokenizers urca utf8 vctrs viridisLite withr zoo

Citation

Development and contributors

Readme and manuals

Help Manual

Help page	Topics
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
ComputeSplus	ComputeSplus
CP2MFAnormedCP	CP2MFAnormedCP
CP2NuclearNormedCP	CP2NuclearNormedCP
CP2SUMPCAnormedCP	CP2SUMPCAnormedCP
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 matrix	DblCenterDist
Dist2CP	Dist2CP
Four computer algorithms evaluate the similarity of six faces for distatis analysis	DistAlgo
'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
GetCmat	GetCmat
GetRectCmat	GetRectCmat
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 analysis	GraphDistatisCompromise
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 analysis	GraphDistatisRv
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
MFAnormCP	MFAnormCP
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 samples	multiculturalSortingSpices
NuclearNormedCP	NuclearNormedCP
'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 matrices	rv
A variation over the base 'R' scale function that avoids the "divide by 0 = NA" problem.	scale1
Ten Assessors sorted eight beers for 'distatis' analysis	Sort SortingBeer
21 French assessors sorted 16 blends of Spice for 'distatis' analysis	SortingSpice SortSpice
Novices and wines experts sort red, rosé, and white wines	sortingWines
SUMPCAnormCP	SUMPCAnormCP
Supplementary element(s) projection in DISTATIS	supplementalProjection4distatis
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