cluscata {ClustBlock}R Documentation

Perform a cluster analysis of blocks of binary variables from a CATA experiment


Hierarchical clustering of blocks of binary data from a CATA experiment. Each cluster of blocks is associated with a compromise computed by the CATATIS method. The hierarchical clustering is followed by a partitioning algorithm (consolidation)


cluscata(Data, nblo, NameBlocks=NULL, NameVar=NULL, Noise_cluster=FALSE,
        Itermax=30, Graph_dend=TRUE, Graph_bar=TRUE, printlevel=FALSE,
        gpmax=min(6, nblo-2), Testonlyoneclust=TRUE, alpha=0.05, nperm=50, Warnings=FALSE)



data frame or matrix where the blocks of binary variables are merged horizontally. If you have a different format, see change_cata_format


numerical. Number of blocks (subjects).


string vector. Name of each block (subject). Length must be equal to the number of blocks. If NULL, the names are S1,...Sm. Default: NULL


string vector. Name of each variable (attribute, the same names for each subject). Length must be equal to the number of attributes. If NULL, the colnames of the first block are taken. Default: NULL


logical. Should a noise cluster be computed? Default: FALSE


numerical. Maximum of iteration for the partitioning algorithm. Default:30


logical. Should the dendrogram be plotted? Default: TRUE


logical. Should the barplot of the difference of the criterion and the barplot of the overall homogeneity at each merging step of the hierarchical algorithm be plotted? Default: TRUE


logical. Print the number of remaining levels during the hierarchical clustering algorithm? Default: FALSE


logical. What is maximum number of clusters to consider? Default: min(6, nblo-2)


logical. Test if there is more than one cluster? Default: TRUE


numerical between 0 and 1. What is the threshold to test if there is more than one cluster? Default: 0.05


numerical. How many permutations are required to test if there is more than one cluster? Default: 50


logical. Display warnings about the fact that none of the subjects in some clusters checked an attribute or product? Default: FALSE


Each partitionK contains a list for each number of clusters of the partition, K=1 to gpmax with:

There is also at the end of the list:


Llobell, F., Cariou, V., Vigneau, E., Labenne, A., & Qannari, E. M. (2019). A new approach for the analysis of data and the clustering of subjects in a CATA experiment. Food Quality and Preference, 72, 31-39.
Llobell, F., Giacalone, D., Labenne, A., Qannari, E.M. (2019). Assessment of the agreement and cluster analysis of the respondents in a CATA experiment. Food Quality and Preference, 77, 184-190.

See Also

plot.cluscata, summary.cluscata , catatis, cluscata_kmeans, change_cata_format


#with 40 subjects
res=cluscata(Data=straw[,1:(16*40)], nblo=40)
plot(res, ngroups=3, Graph_dend=FALSE)
summary(res, ngroups=3)
#With noise cluster
res2=cluscata(Data=straw[,1:(16*40)], nblo=40, Noise_cluster=TRUE,
Graph_dend=FALSE, Graph_bar=FALSE)
#with all subjects
res=cluscata(Data=straw, nblo=114, printlevel=TRUE)

[Package ClustBlock version 2.4.0 Index]