Published by the Foundation for Open Access Statistics Editors-in-chief: Bettina Grün, Torsten Hothorn, Rebecca Killick, Edzer Pebesma, Achim Zeileis    ISSN 1548-7660; CODEN JSSOBK
Authors: Parmeet Singh Bhatia, Serge Iovleff, Gérard Govaert
Title: blockcluster: An R Package for Model-Based Co-Clustering
Abstract: 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.

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Paper: blockcluster: An R Package for Model-Based Co-Clustering     Download PDF (Downloads: 1936)
blockcluster_4.2.3.tar.gz: R source package Download (Downloads: 155; 1MB)
v76i09.R: R replication code Download (Downloads: 173; 2KB) Replication materials Download (Downloads: 95; 420KB)

DOI: 10.18637/jss.v076.i09

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Paper: Creative Commons Attribution 3.0 Unported License
Code: GNU General Public License (at least one of version 2 or version 3) or a GPL-compatible license.