Article
biclustermd: An R Package for Biclustering with Missing Values
The R Journal
Document Type
Article
Disciplines
Publication Version
Accepted Manuscript
Publication Date
1-1-2019
Abstract
Biclustering is a statistical learning technique that attempts to find homogeneous partitions of rows and columns of a data matrix. For example, movie ratings might be biclustered to group both raters and movies. biclust is a current R package allowing users to implement a variety of biclustering algorithms. However, its algorithms do not allow the data matrix to have missing values. We provide a new R package, biclustermd, which allows users to perform biclustering on numeric data even in the presence of missing values.
Creative Commons License
Creative Commons Attribution 4.0 International
Copyright Owner
The Author(s)
Copyright Date
2019
Language
en
File Format
application/pdf
Citation Information
John Reisner, Hieu Pham, Sigurdur Olafsson, Stephen B. Vardeman, et al.. "biclustermd: An R Package for Biclustering with Missing Values" The R Journal (2019) Available at: http://works.bepress.com/stephen_vardeman/41/
This is a manuscript of an article published as Reisner, John, Hieu Pham, Sigurdur Olafsson, Stephen Vardeman, and Jing Li. "biclustermd: An R Package for Biclustering with Missing Values." (2019). Posted with permission.