Package: dad 4.1.5

Pierre Santagostini

dad: Three-Way / Multigroup Data Analysis Through Densities

The data consist of a set of variables measured on several groups of individuals. To each group is associated an estimated probability density function. The package provides tools to create or manage such data and functional methods (principal component analysis, multidimensional scaling, cluster analysis, discriminant analysis...) for such probability densities.

Authors:Rachid Boumaza [aut], Pierre Santagostini [aut, cre], Smail Yousfi [aut], Gilles Hunault [ctb], Julie Bourbeillon [ctb], Besnik Pumo [ctb], Sabine Demotes-Mainard [aut]

dad_4.1.5.tar.gz
dad_4.1.5.tar.gz(r-4.5-noble)dad_4.1.5.tar.gz(r-4.4-noble)
dad_4.1.5.tgz(r-4.4-emscripten)dad_4.1.5.tgz(r-4.3-emscripten)
dad.pdf |dad.html✨
dad/json (API)

# Install 'dad' in R:
install.packages('dad', repos = '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.

4.36 score 23k downloads 144 exports 66 dependencies

Last updated 4 months agofrom:95e41b95c7. Checks:2 OK, 1 NOTE. Indexed: no.

TargetResultLatest binary
Doc / VignettesOKMar 28 2025
R-4.5-linuxOKMar 28 2025
R-4.4-linuxNOTEMar 28 2025

Exports:appendtofolderhas.data.frame.folderas.data.frame.folderhas.data.frame.foldertas.folderas.folder.data.frameas.folder.folderhas.folderhas.folderh.foldermtgas.foldertas.foldert.arrayas.foldert.data.framebandwidth.parametercor.foldercramer.data.framecramer.foldercut.data.framecut.folderddchisqsymddchisqsymparddhellingerddhellingerparddjeffreysddjeffreysparddjensenddjensenparddlpddlppardiscdd.misclassdiscdd.predictdistl2ddistl2dnormdistl2dnormpardistl2dpardstatis.interfdiscd.misclassfdiscd.predictfhclustdfmdsdfolderfolderhfoldertfpcadfpcatgetcol.foldergetcol.foldertgetrow.foldergetrow.folderthclustddhellingerhellingerparinterpretinterpret.dstatisinterpret.fmdsdinterpret.fpcadinterpret.fpcatinterpret.mdsddis.discdd.misclassis.discdd.predictis.dstatisis.fdiscd.misclassis.fdiscd.predictis.fhclustdis.fmdsdis.folderis.folderhis.foldermtgis.foldertis.fpcadis.mdsddjeffreysjeffreysparkurtosis.folderl2dl2dparmatddchisqsymmatddchisqsymparmatddhellingermatddhellingerparmatddjeffreysmatddjeffreysparmatddjensenmatddjensenparmatddlpmatddlpparmatdistl2dmatdistl2dnormmatdistl2dnormparmatdistl2dparmathellingermathellingerparmatipl2dmatipl2dparmatjeffreysmatjeffreysparmatwassersteinmatwassersteinparmdsddmean.foldermtgcomponentsmtgordermtgrankpearson.data.framepearson.folderphi.data.framephi.folderplot.dstatisplot.fhclustdplot.fmdsdplot.foldertplot.fpcadplot.fpcatplot.hclustddplot.mdsddplotframesprint.discdd.misclassprint.discdd.predictprint.dstatisprint.fdiscd.misclassprint.fdiscd.predictprint.fhclustdprint.fmdsdprint.foldermtgprint.foldertprint.fpcadprint.fpcatprint.hclustddprint.mdsddread.mtgrmcol.folderrmcol.foldertrmrow.folderrmrow.foldertskewness.foldersqrtmatrixsummary.foldersummary.folderhsummary.foldermtgsummary.folderttschuprow.data.frametschuprow.foldervar.folderwassersteinwassersteinpar

Dependencies:askpassbitbit64bootcellrangerclassclicliprcolorspacecpp11crayoncurldata.tableDescToolse1071Exactexpmfansifarverforcatsggplot2gldgluegtablehavenhmshttrisobandjsonlitelabelinglatticelifecyclelmommagrittrMASSMatrixmgcvmimemunsellmvtnormnlmeopensslpillarpkgconfigprettyunitsprogressproxyR6RColorBrewerRcppreadrreadxlrematchrlangrootSolverstudioapiscalessystibbletidyselecttzdbutf8vctrsviridisLitevroomwithr

Introduction to dad

Pierre Santagostini, Rachid Boumaza

Rendered fromdad-intro.Rmdusingknitr::rmarkdownon Mar 28 2025.

Last update: 2024-11-22
Started: 2020-07-15

Multidimensional Scaling of Discrete Probability Distributions

Pierre Santagostini, Rachid Boumaza

Rendered frommds-discrete-distributions.Rmdusingknitr::rmarkdownon Mar 28 2025.

Last update: 2024-11-22
Started: 2020-07-15

Citation

Boumaza R, Santagostini P, Yousfi S, Demotes-Mainard S (2021). “dad: an R Package for Visualisation, Classification and Discrimination of Multivariate Groups Modelled by their Densities.” The R Journal, 13(2), 386. doi:10.32614/RJ-2021-071.

Corresponding BibTeX entry: 

  @Article{,
    title = {dad: an R Package for Visualisation, Classification and
      Discrimination of Multivariate Groups Modelled by their
      Densities},
    author = {Rachid Boumaza and Pierre Santagostini and Smail Yousfi
      and Sabine Demotes-Mainard},
    journal = {The R Journal},
    year = {2021},
    volume = {13},
    number = {2},
    pages = {386},
    doi = {10.32614/RJ-2021-071},
  }

Readme and manuals

dad

The data consist of a set of variables measured on several groups of individuals. To each group is associated an estimated probability density function. The R package {dad} provides tools to create or manage such data and functional methods (principal component analysis, multidimensional scaling, cluster analysis, discriminant analysis...) for such probability densities.

Rachid Boumaza, Pierre Santagostini, Smail Yousfi and Sabine Demotes-Mainard, https://journal.r-project.org/archive/2021/RJ-2021-071/index.html, The R Journal (2021) 13:2, pages 179--207, DOI: 10.32614/RJ-2021-071

Installation

Install the package from the CRAN:

install.packages("dad")

Or from the repository, using the devtools package:

install.packages("devtools")
devtools::install_git("https://forgemia.inra.fr/dad/dad.git", build_vignettes = TRUE)

Help Manual

Help pageTopics
Three-Way Data Analysis Through Densitiesdad-package dad
Adds a data frame to a 'folderh'.appendtofolderh
Folder to data frameas.data.frame.folder
Hierarchic folder to data frameas.data.frame.folderh
foldert to data frameas.data.frame.foldert
Coerce to a folderas.folder
Data frame to folderas.folder.data.frame
Hierarchic folder to folderas.folder.folderh
Coerce to a folderhas.folderh
Build a hierarchic folder from an object of class foldermtgas.folderh.foldermtg
Coerce to a foldertas.foldert
Data frame to foldertas.foldert.array
Data frame to foldertas.foldert.data.frame
Association measures between several categorical variables of a data framecramer.data.frame pearson.data.frame phi.data.frame tschuprow.data.frame
Association measures between categorical variables of the data frames of a foldercramer.folder pearson.folder phi.folder tschuprow.folder
Parameter of the normal reference rulebandwidth.parameter
Alsacian castles by year of buildingcastles
Dated Alsacian castlescastles.dated
Non dated Alsacian castlescastles.nondated
Correlation matrices of a folder of data setscor.folder
Change numeric variables into factorscut.data.frame
In a folder: change numeric variables into factorscut.folder
Distance between probability distributions of discrete variables given samplesddchisqsym
Distance between discrete probability distributions given the probabilities on their common supportddchisqsympar
Distance between probability distributions of discrete variables given samplesddhellinger
Distance between discrete probability distributions given the probabilities on their common supportddhellingerpar
Divergence between probability distributions of discrete variables given samplesddjeffreys
Distance between discrete probability distributions given the probabilities on their common supportddjeffreyspar
Divergence between probability distributions of discrete variables given samplesddjensen
Divergence between discrete probability distributions given the probabilities on their common supportddjensenpar
Distance between probability distributions of discrete variables given samplesddlp
Distance between discrete probability distributions given the probabilities on their common supportddlppar
French departments and regionsdepartments
Misclassification ratio in functional discriminant analysis of discrete probability distributions.discdd.misclass
Predicting the class of a group of individuals with discriminant analysis of probability distributions.discdd.predict
L^2 distance between probability densitiesdistl2d
L^2 distance between L^2-normed probability densitiesdistl2dnorm
L^2 distance between L^2-normed Gaussian densities given their parametersdistl2dnormpar
L^2 distance between Gaussian densities given their parametersdistl2dpar
Diploma x Socio professional groupdspg
Diploma x Socio professional group by departement in 2015dspgd2015
Dual STATIS method (interstructure stage)dstatis dstatis.inter
Misclassification ratio in functional discriminant analysis of probability densities.fdiscd.misclass
Predicting the class of a group of individuals with discriminant analysis of probability densities.fdiscd.predict
Hierarchic cluster analysis of probability densitiesfhclustd
Rose floweringfloribundity
Multidimensional scaling of probability densitiesfmdsd
Folder of data setsfolder
Hierarchic folder of n data frames related in pairs by (n-1) keysfolderh
foldermtgfoldermtg
Folder of data sets among timefoldert
Functional PCA of probability densitiesfpcad
Functional PCA of probability densities among timefpcat
Select columns in all elements of a foldergetcol.folder
Select columns in all elements of a foldertgetcol.foldert
Select rows in all elements of a foldergetrow.folder
Select rows in all elements of a foldertgetrow.foldert
Hierarchic cluster analysis of discrete probability distributionshclustdd
Hellinger distance between Gaussian densitieshellinger
Hellinger distance between Gaussian densities given their parametershellingerpar
Scores of 'fmdsd', 'dstatis', 'fpcad', or 'fpcat' vs. moments, or scores of 'mdsdd' vs. marginal distributions or association measuresinterpret
Scores of the 'dstatis' function vs. moments of the densitiesinterpret.dstatis
Scores of the 'fmdsd' function vs. moments of the densitiesinterpret.fmdsd
Scores of the 'fpcad' function vs. moments of the densitiesinterpret.fpcad
Scores of the '"fpcat"' function vs. moments of the densitiesinterpret.fpcat
Scores of the 'mdsdd' function vs. marginal probability distributions or association measuresinterpret.mdsdd
Class 'discdd.misclass'is.discdd.misclass
Class 'discdd.predict'is.discdd.predict
Class 'dstatis'is.dstatis
Class 'fdiscd.misclass'is.fdiscd.misclass
Class 'fdiscd.predict'is.fdiscd.predict
Class 'fhclustd'is.fhclustd
Class 'fmdsd'is.fmdsd
Class 'folder'is.folder
Class 'folderh'is.folderh
Class 'foldermtg'is.foldermtg
Class 'foldert'is.foldert
Class 'fpcad'is.fpcad
Class 'mdsdd'is.mdsdd
Jeffreys measure between Gaussian densitiesjeffreys
Jeffreys measure between Gaussian densities given their parametersjeffreyspar
Kurtosis coefficients of a folder of data setskurtosis.folder
L^2 inner product of probability densitiesl2d
L^2 inner product of Gaussian densities given their parametersl2dpar
Matrix of distances between discrete probability densities given samplesmatddchisqsym
Matrix of distances between discrete probability densities given the probabilities on their common supportmatddchisqsympar
Matrix of distances between discrete probability densities given samplesmatddhellinger
Matrix of distances between discrete probability densities given the probabilities on their common supportmatddhellingerpar
Matrix of distances between discrete probability densities given samplesmatddjeffreys
Matrix of divergences between discrete probability densities given the probabilities on their common supportmatddjeffreyspar
Matrix of divergences between discrete probability densities given samplesmatddjensen
Matrix of divergences between discrete probability densities given the probabilities on their common supportmatddjensenpar
Matrix of distances between discrete probability distributions given samplesmatddlp
Matrix of distances between discrete probability densities given the probabilities on their common supportmatddlppar
Matrix of L^2 distances between probability densitiesmatdistl2d
Matrix of L^2 distances between L^2-normed probability densitiesmatdistl2dnorm
Matrix of L^2 distances between L^2-normed Gaussian densities given their parametersmatdistl2dnormpar
Matrix of L^2 distances between Gaussian densities given their parametersmatdistl2dpar
Matrix of Hellinger distances between Gaussian densitiesmathellinger
Matrix of Hellinger distances between Gaussian densities given their parametersmathellingerpar
Matrix of L^2 inner products of probability densitiesmatipl2d
Matrix of L^2 inner products of Gaussian densitiesmatipl2dpar
Matrix of the Jeffreys measures (symmetrised Kullback-Leibler divergences) between Gaussian densitiesmatjeffreys
Matrix of Jeffreys measures (symmetrised Kullback-Leibler divergences) between Gaussian densitiesmatjeffreyspar
Matrix of 2-Wassterstein distance between Gaussian densitiesmatwasserstein
Matrix of 2-Wasserstein distances between Gaussian densitiesmatwassersteinpar
Multidimensional scaling of discrete probability distributionsmdsdd
Means of a folder of data setsmean.folder
Components of upper scale of a vertexmtgcomponents
Branching order of verticesmtgorder
Class 'foldermtg'mtgplant1
Class 'foldermtg'mtgplant2
Ranks of vertices in a decompositionmtgrank
Plotting scores of STATIS method (interstructure) analysisplot.dstatis
Plotting a hierarchical clusteringplot.fhclustd
Plotting scores of multidimensional scaling of density functionsplot.fmdsd
Plotting data of a foldertplot.foldert
Plotting scores of principal component analysis of density functionsplot.fpcad
Plotting scores of principal component analysis of density functions among timeplot.fpcat
Plotting a hierarchical clustering of discrete distributionsplot.hclustdd
Plotting scores of multidimensional scaling analysis of discrete distributionsplot.mdsdd
Plotting of two sets of variablesplotframes
Printing results of discriminant analysis of discrete probability distributionsprint.discdd.misclass
Printing results of discriminant analysis of discrete probability distributionsprint.discdd.predict
Printing results of STATIS method (interstructure) analysisprint.dstatis
Printing results of discriminant analysis of probability density functionsprint.fdiscd.misclass
Printing results of discriminant analysis of probability density functionsprint.fdiscd.predict
Printing results of a hierarchical clustering of probability density functionsprint.fhclustd
Printing results of a multidimensional scaling analysis of probability densitiesprint.fmdsd
Printing an object of class 'foldermtg'print.foldermtg
Printing an object of class 'foldert'print.foldert
Printing results of a functional PCA of probability densitiesprint.fpcad
Printing results of a functional PCA of probability densities among timeprint.fpcat
Printing results of a hierarchical clustering of discrete distributionsprint.hclustdd
Printing results of a multidimensional scaling analysis of discrete distributionsprint.mdsdd
Read a MTG (Multiscale Tree Graph) fileread.mtg topology
Remove columns in all elements of a folderrmcol.folder
Remove cols in all elements of a foldertrmcol.foldert
Remove rows in all elements of a folderrmrow.folder
Remove rows in all elements of a foldertrmrow.foldert
Rose flowersroseflowers
Rose leavesroseleaves
Rose leaf and internode dynamicsrosephytomer
Roses dataroses
Skewness coefficients of a folder of data setsskewness.folder
Square root of a symmetric, positive semi-definite matrixsqrtmatrix
Summarize a foldersummary.folder
Summarize a folderhsummary.folderh
Summary of an object of class 'foldermtg'summary.foldermtg
Summarize a foldertsummary.foldert
Variance matrices of a folder of data setsvar.folder
Rose variety leavesvarietyleaves
2-Wasserstein distance between Gaussian densitieswasserstein
2-Wasserstein distance between Gaussian densities given their parameterswassersteinpar