TY - JOUR AU - Bhatia, Parmeet Singh AU - Iovleff, Serge AU - Govaert, GĂ©rard PY - 2017/02/27 Y2 - 2024/03/28 TI - blockcluster: An R Package for Model-Based Co-Clustering JF - Journal of Statistical Software JA - J. Stat. Soft. VL - 76 IS - 9 SE - Articles DO - 10.18637/jss.v076.i09 UR - https://www.jstatsoft.org/index.php/jss/article/view/v076i09 SP - 1 - 24 AB - Simultaneous clustering of rows and columns, usually designated by bi-clustering, coclustering or block clustering, is an important technique in two way data analysis. A new standard and efficient approach has been recently proposed based on the latent block model (Govaert and Nadif 2003) which takes into account the block clustering problem on both the individual and variable sets. This article presents our R package blockcluster for co-clustering of binary, contingency and continuous data based on these very models. In this document, we will give a brief review of the model-based block clustering methods, and we will show how the R package blockcluster can be used for co-clustering. ER -