- Journal
- JOURNAL OF STATISTICAL SOFTWARE
- Année
- 2017
- Volume
- 76
- Numéro
- 9
- Pages
- 1-24
- Mois
- FEB
- DOI
- 10.18637/jss.v076.i09
Abstract
Simultaneous clustering of rows and columns, usually designated by bi-clustering, co-clustering 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.