biclustermd: Biclustering with Missing Data

Biclustering is a statistical learning technique that simultaneously partitions and clusters rows and columns of a data matrix. Since the solution space of biclustering is in infeasible to completely search with current computational mechanisms, this package uses a greedy heuristic. The algorithm featured in this package is, to the best our knowledge, the first biclustering algorithm to work on data with missing values. Li, J., Reisner, J., Pham, H., Olafsson, S., and Vardeman, S. (2020) Biclustering with Missing Data. Information Sciences, 510, 304–316.

Version: 0.2.3
Depends: ggplot2 (≥ 3.0.0), R (≥ 3.5.0), tidyr (≥ 0.8.1)
Imports: biclust (≥ 2.0.1), doParallel (≥ 1.0.14), dplyr (≥ 0.7.6), foreach (≥ 1.4.4), magrittr (≥ 1.5), nycflights13 (≥ 1.0.0), phyclust (≥ 0.1-24)
Suggests: knitr, rmarkdown, testthat
Published: 2021-06-17
Author: John Reisner [cre, aut, cph], Hieu Pham [ctb, cph], Jing Li [ctb, cph]
Maintainer: John Reisner <johntreisner at>
License: MIT + file LICENSE
NeedsCompilation: no
Materials: README
In views: MissingData
CRAN checks: biclustermd results


Reference manual: biclustermd.pdf
Vignettes: Biclustering Airport Delay Data


Package source: biclustermd_0.2.3.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): biclustermd_0.2.3.tgz, r-release (x86_64): biclustermd_0.2.3.tgz, r-oldrel: biclustermd_0.2.3.tgz
Old sources: biclustermd archive


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