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 gmail.com> |
| BugReports: |
https://github.com/jreisner/biclustermd/issues |
| License: |
MIT + file LICENSE |
| URL: |
https://github.com/jreisner/biclustermd |
| NeedsCompilation: |
no |
| Materials: |
README |
| In views: |
MissingData |
| CRAN checks: |
biclustermd results |
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