LUCIDus: Latent Unknown Clustering with Integrated Data

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: 0.9.0
Depends: R (≥ 3.1.0)
Imports: mvtnorm, nnet, glmnet, glasso, Matrix, lbfgs, stats, methods, networkD3, foreach, doParallel
Suggests: testthat, knitr, rmarkdown
Published: 2018-12-21
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
Materials: README
CRAN checks: LUCIDus results

Downloads:

Reference manual: LUCIDus.pdf
Vignettes: LUCIDus
Package source: LUCIDus_0.9.0.tar.gz
Windows binaries: r-devel: LUCIDus_0.9.0.zip, r-release: LUCIDus_0.9.0.zip, r-oldrel: LUCIDus_0.9.0.zip
OS X binaries: r-release: LUCIDus_0.9.0.tgz, r-oldrel: LUCIDus_0.9.0.tgz

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