Published by the Foundation for Open Access Statistics
Editors-in-chief: Bettina Grün, Torsten Hothorn, Edzer Pebesma, Achim Zeileis    ISSN 1548-7660; CODEN JSSOBK
blockcluster: An R Package for Model-Based Co-Clustering | Bhatia | Journal of Statistical Software
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.

Page views:: 794. Submitted: 2015-02-06. Published: 2017-02-27.
Paper: blockcluster: An R Package for Model-Based Co-Clustering     Download PDF (Downloads: 345)
Supplements:
blockcluster_4.2.3.tar.gz: R source package Download (Downloads: 27; 1MB)
v76i09.R: R replication code Download (Downloads: 24; 2KB)
v76i09-replication.zip: Replication materials Download (Downloads: 15; 420KB)

DOI: 10.18637/jss.v076.i09

by
This work is licensed under the licenses
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.