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iClusterVB: Fast Integrative Clustering and Feature Selection for High
Dimensional Data
A variational Bayesian approach for fast integrative
clustering and feature selection, facilitating the analysis of
multi-view, mixed type, high-dimensional datasets with applications in
fields like cancer research, genomics, and more.
| Version: |
0.1.4 |
| Depends: |
R (≥ 4.0.0) |
| Imports: |
cluster, clustMixType, cowplot, ggplot2, graphics, grDevices, mclust, MCMCpack, mvtnorm, pheatmap, poLCA, Rcpp (≥ 1.0.12), stats, utils, VarSelLCM |
| LinkingTo: |
Rcpp, RcppArmadillo |
| Suggests: |
knitr, rmarkdown, survival, survminer |
| Published: |
2024-12-09 |
| DOI: |
10.32614/CRAN.package.iClusterVB |
| Author: |
Abdalkarim Alnajjar
 [aut, cre,
cph],
Zihang Lu [aut] |
| Maintainer: |
Abdalkarim Alnajjar <abdalkarim.alnajjar at queensu.ca> |
| BugReports: |
https://github.com/AbdalkarimA/iClusterVB/issues |
| License: |
MIT + file LICENSE |
| URL: |
https://github.com/AbdalkarimA/iClusterVB |
| NeedsCompilation: |
yes |
| Materials: |
README |
| CRAN checks: |
iClusterVB results |
Documentation:
Downloads:
Linking:
Please use the canonical form
https://CRAN.R-project.org/package=iClusterVB
to link to this page.
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.