bikm1-package {bikm1}R Documentation

bikm1 package


This package is designed to co-cluster a contingency (resp. binary) matrix, or double binary matrices in blocks respectively under the (normalized or not) Poisson (resp binary) Latent Block Model and the Multiple Latent Block Model. It enables to automatically select the number of row and column clusters and to compare partition estimations with reference partitions.


Package for the segmentation of the rows and columns inducing a co-clustering and automatically select the number of row and column clusters.

Model 1

BIKM1_LBM_Poisson . This fitting procedure produces a BIKM1_LBM_Poisson object.

Model 2

BIKM1_LBM_Binary . This fitting procedure produces a BIKM1_LBM_Binary object.

Model 3

BIKM1_MLBM_Binary . This fitting procedure produces a BIKM1_MLBM_Binary object.

Technical remarks

Display of the result with plot,BIKM1_LBM_Poisson-method and

with show,BIKM1_LBM_Poisson-method, with summary,BIKM1_LBM_Poisson-method and with print,BIKM1_LBM_Poisson-method.

Display of the result with plot,BIKM1_LBM_Binary-method and

with show,BIKM1_LBM_Binary-method, with summary,BIKM1_LBM_Binary-method and with print,BIKM1_LBM_Binary-method.

Display of the result with plot,BIKM1_MLBM_Binary-method and

with show,BIKM1_MLBM_Binary-method, with summary,BIKM1_MLBM_Binary-method and with print,BIKM1_MLBM_Binary-method.


Valerie Robert


Keribin, Celeux and Robert, The Latent Block Model: a useful model for high dimensional data.

Govaert and Nadif. Co-clustering, Wyley (2013).

Keribin, Brault and Celeux. Estimation and Selection for the Latent Block Model on Categorical Data, Statistics and Computing (2014).

Robert. Classification croisee pour l'analyse de bases de donnees de grandes dimensions de pharmacovigilance. Thesis, Paris Saclay (2017).

Robert, Vasseur and Brault. Comparing high dimensional partitions with the Co-clustering Adjusted Rand Index, Journal of Classification, 38(1), 158-186 (2021).

[Package bikm1 version 1.1.0 Index]