An implementation for the 'LUCID' method to jointly estimate latent unknown clusters/subgroups with integrated data. An EM algorithm is used to obtain the latent cluster assignment and model parameter estimates. Feature selection is achieved by applying the regularization method.
Version: | 1.0.0 |
Depends: | R (≥ 3.1.0) |
Imports: | mvtnorm, nnet, glmnet, glasso, Matrix, lbfgs, stats, methods, boot, networkD3, foreach, doParallel |
Suggests: | testthat, knitr, rmarkdown |
Published: | 2019-12-02 |
Author: | Cheng Peng, Zhao Yang, David V. Conti |
Maintainer: | Cheng Peng <chengpen at usc.edu> |
License: | GPL-2 |
URL: | https://github.com/USCbiostats/LUCIDus |
NeedsCompilation: | no |
Citation: | LUCIDus citation info |
Materials: | README NEWS |
CRAN checks: | LUCIDus results |
Reference manual: | LUCIDus.pdf |
Vignettes: |
LUCIDus |
Package source: | LUCIDus_1.0.0.tar.gz |
Windows binaries: | r-devel: LUCIDus_1.0.0.zip, r-devel-gcc8: LUCIDus_1.0.0.zip, r-release: LUCIDus_1.0.0.zip, r-oldrel: LUCIDus_1.0.0.zip |
OS X binaries: | r-release: LUCIDus_1.0.0.tgz, r-oldrel: LUCIDus_1.0.0.tgz |
Old sources: | LUCIDus archive |
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