Campus Units

Industrial and Manufacturing Systems Engineering, Statistics

Document Type

Article

Publication Version

Accepted Manuscript

Publication Date

2019

Journal or Book Title

The R Journal

Research Focus Area(s)

Information Engineering

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.

Comments

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.

Creative Commons License

Creative Commons Attribution 4.0 License
This work is licensed under a Creative Commons Attribution 4.0 License.

Copyright Owner

The Author(s)

Language

en

File Format

application/pdf

Published Version

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