Package: CAinterprTools 1.1.0

CAinterprTools: Graphical Aid in Correspondence Analysis Interpretation and Significance Testings

Allows to plot a number of information related to the interpretation of Correspondence Analysis' results. It provides the facility to plot the contribution of rows and columns categories to the principal dimensions, the quality of points display on selected dimensions, the correlation of row and column categories to selected dimensions, etc. It also allows to assess which dimension(s) is important for the data structure interpretation by means of different statistics and tests. The package also offers the facility to plot the permuted distribution of the table total inertia as well as of the inertia accounted for by pairs of selected dimensions. Different facilities are also provided that aim to produce interpretation-oriented scatterplots. Reference: Alberti 2015 <doi:10.1016/j.softx.2015.07.001>.

Authors:Gianmarco Alberti [aut, cre]

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CAinterprTools.pdf |CAinterprTools.html✨
CAinterprTools/json (API)
NEWS

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

Peer review:

Datasets:
  • brand_coffee - Dataset: Cross-tabulation of coffee brands vs. consumers' opinion
  • breakfast - Dataset: Cross-tabulation of breakfast food vs consumers' opinion
  • diseases - Dataset: Cross-tabulation of quantity of tobacco smoked daily vs. cause of death
  • fire_loss - Dataset: Cross-tabulation of cause of fire vs. amount of money loss
  • greenacre_data - Dataset: Cross-tabulation of funding category vs. University faculty

On CRAN:

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

2.52 score 33 scripts 260 downloads 2 mentions 24 exports 136 dependencies

Last updated 4 years agofrom:35b5f6512c. Checks:OK: 7. Indexed: yes.

TargetResultDate
Doc / VignettesOKOct 27 2024
R-4.5-winOKSep 27 2024
R-4.5-linuxOKOct 27 2024
R-4.4-winOKOct 27 2024
R-4.4-macOKOct 27 2024
R-4.3-winOKOct 27 2024
R-4.3-macOKOct 27 2024

Exports:aver.rulecaClustercaCorrcaPerceptcaPlotcaPluscaScattercols.cntrcols.cntr.scattercols.corrcols.corr.scattercols.qltgroupBycoordmalinvaudrescalerows.cntrrows.cntr.scatterrows.corrrows.corr.scatterrows.qltsig.dim.permsig.dim.perm.screesig.tot.inertia.permtable.collapse

Dependencies:abindbackportsbase64encbitbit64bootbroombslibcacachemcarcarDatacellrangercheckmateclassclassIntclicliprclustercolorspacecowplotcpp11crayoncrosstalkdata.tableDerivdigestdoBydplyrDTe1071ellipseemmeansestimabilityevaluateFactoMineRfansifarverfastmapflashClustfontawesomeforcatsforeignFormulafsgenericsggplot2ggrepelgluegridExtragtablehavenhighrHmischmshtmlTablehtmltoolshtmlwidgetshttpuvisobandjquerylibjsonliteKernSmoothknitrlabelinglaterlatticelazyevalleapslifecyclelme4magrittrMASSMatrixMatrixModelsmemoisemgcvmicrobenchmarkmimeminqamodelrmultcompViewmunsellmvtnormnlmenloptrnnetnortestnumDerivpbkrtestpillarpkgconfigplyrprettyunitsprogresspromisesproxypurrrquantregR6rappdirsRcmdrMiscRColorBrewerRcppRcppEigenreadrreadstata13readxlrematchreshape2rlangrmarkdownrpartrstudioapisandwichsassscalesscatterplot3dSparseMstringistringrsurvivaltibbletidyrtidyselecttinytextzdbutf8vctrsviridisviridisLitevroomwithrxfunyamlzoo

Readme and manuals

Help Manual

Help pageTopics
Package for Graphical Aid in Correspondence Analysis Interpretation and Significance TestingsCAinterprTools-package CAinterprTools
Average Rule chartaver.rule
Dataset: Cross-tabulation of coffee brands vs. consumers' opinionbrand_coffee
Dataset: Cross-tabulation of breakfast food vs consumers' opinionbreakfast
Clustering row/column categories on the basis of Correspondence Analysis coordinates from a space of user-defined dimensionality.caCluster
Chart of correlation between rows and columns categoriescaCorr
Perceptual map-like Correspondence Analysis scatterplotcaPercept
Intepretation-oriented Correspondence Analysis scatterplots, with informative and flexible (non-overlapping) labels.caPlot
Facility for interpretation-oriented CA scatterplotcaPlus
Scatterplot visualization facilitycaScatter
Columns contribution chartcols.cntr
Scatterplot for column categories contribution to dimensionscols.cntr.scatter
Chart of columns correlation with a selected dimensioncols.corr
Scatterplot for column categories correlation with dimensionscols.corr.scatter
Chart of columns quality of the displaycols.qlt
Dataset: Cross-tabulation of quantity of tobacco smoked daily vs. cause of deathdiseases
Dataset: Cross-tabulation of cause of fire vs. amount of money lossfire_loss
Dataset: Cross-tabulation of funding category vs. University facultygreenacre_data
Define groups of categories on the basis of a selected partition into k groups employing the Jenks' natural break method on the selected dimension's coordinatesgroupBycoord
Malinvaud's test for significance of the CA dimensionsmalinvaud
Rescaling row/column categories coordinates between a minimum and maximum valuerescale
Rows contribution chartrows.cntr
Scatterplot for row categories contribution to dimensionsrows.cntr.scatter
Chart of rows correlation with a selected dimensionrows.corr
Scatterplot for row categories correlation with dimensionsrows.corr.scatter
Chart of rows quality of the displayrows.qlt
Permuted significance of CA dimensionssig.dim.perm
Scree plot to test the significance of CA dimensions by means of a randomized proceduresig.dim.perm.scree
Permuted significance of the CA total inertiasig.tot.inertia.perm
Collapse rows and columns of a table on the basis of hierarchical clusteringtable.collapse