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ClustBlock (version 4.1.1)

Clustering of Datasets

Description

Hierarchical and partitioning algorithms to cluster blocks of variables. The partitioning algorithm includes an option called noise cluster to set aside atypical blocks of variables. Different thresholds per cluster can be sets. The CLUSTATIS method (for quantitative blocks) (Llobell, Cariou, Vigneau, Labenne & Qannari (2020) , Llobell, Vigneau & Qannari (2019) ) and the CLUSCATA method (for Check-All-That-Apply data) (Llobell, Cariou, Vigneau, Labenne & Qannari (2019) , Llobell, Giacalone, Labenne & Qannari (2019) ) are the core of this package. The CATATIS methods allows to compute some indices and tests to control the quality of CATA data. Multivariate analysis and clustering of subjects for quantitative multiblock data, CATA, RATA, Free Sorting and JAR experiments are available. Clustering of rows in multi-block context (notably with ClusMB strategy) is also included.

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Version

Install

install.packages('ClustBlock')

Monthly Downloads

326

Version

4.1.1

License

MIT + file LICENSE

Maintainer

Fabien Llobell

Last Published

June 11th, 2025

Functions in ClustBlock (4.1.1)

Perform a cluster analysis of subjects in a JAR experiment.

clustatis_FreeSort

Perform a cluster analysis of free sorting data

Perform a cluster analysis of subjects from a RATA experiment

clustatis_FreeSort_kmeans

Compute the CLUSTATIS partitioning algorithm on free sorting data

cluscata_kmeans

Compute the CLUSCATA partitioning algorithm on different blocks from a CATA experiment

cluscata_kmeans_jar

Perform a cluster analysis of subjects in a JAR experiment

Perform a cluster analysis of blocks of quantitative variables

Perform a cluster analysis of subjects from a CATA experiment

clustRowsOnStatisAxes

Perform a cluster analysis of rows in a Multi-block context with clustering on STATIS axes

clustatis_kmeans

Compute the CLUSTATIS partitioning algorithm on different blocks of quantitative variables

Display the STATIS charts

indicesClusters

Compute the indices to evaluate the quality of the cluster partition in multi-block context

Displays the CLUSTATIS graphs

Displays the CLUSCATA graphs

simil_groups_cata

Testing the difference in perception between two predetermined groups of subjects in a CATA experiment

Print the STATIS results

print.clustatis

Print the CLUSTATIS results

Displays the CATATIS graphs

Displays the ClusMB and clustRowsOnstatisAxes graphs

consistency_cata_panel

Test the consistency of the panel in a CATA experiment

summary.clusRows

Show the ClusMB or clustering on STATIS axes results

consistency_cata

Test the consistency of each attribute in a CATA experiment

summary.clustatis

Show the CLUSTATIS results

Print the CLUSCATA results

Show the STATIS results

Print the ClusMB or clustering on STATIS axes results

Performs the STATIS method on different blocks of quantitative variables

statis_FreeSort

Performs the STATIS method on Free Sorting data

summary.cluscata

Show the CLUSCATA results

summary.catatis

Show the CATATIS results

Preprocessing for Just About Right Data

preprocess_FreeSort

Preprocessing for Free Sorting Data

strawberries data

Print the CATATIS results

change_cata_format

Change format of CATA datasets to perform CATATIS or CLUSCATA function

change_cata_format2

Change format of CATA datasets to perform the package functions

Perform the CATATIS method on different blocks from a RATA experiment

Perform the CATATIS method on different blocks from a CATA experiment

ClustBlock-package

Clustering of Datasets

cheese Just About Right data

chocolates data

Perform the CATATIS method on Just About Right data.

RATA data on chocolates

Perform a cluster analysis of rows in a Multi-block context with the ClusMB method