Imports: partykit (>= 1.2.0), rpart, survival, interval,inum

Imports: partykit (>= 1.2.0), rpart, survival, inum, icenReg
Suggests: Formula, rpart.plot, knitr, rmarkdown, interval

Imports: partykit (>= 1.2.0), rpart, survival, inum, icenReg, Icens,
Author: Wei Fu, Jeffrey Simonoff, Wenbo Jing
Packaged: 2021-01-11 01:31:53 UTC; WENBO JING

Title: Latent Unknown Clustering with Integrated Data
Author: Cheng Peng, Zhao Yang, David V. Conti
Description: 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.
Imports: mvtnorm, nnet, glmnet, glasso, Matrix, lbfgs, stats, methods,

Author: Yinqi Zhao, Cheng Peng, Zhao Yang, David V. Conti
Description: An implementation for the 'LUCID' model (Peng (2019) <doi:10.1093/bioinformatics/btz667>) 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 L1 regularization method.
Imports: mclust, nnet, networkD3, parallel, boot, lbfgs, glasso, glmnet

Author: Yinqi Zhao, David V. Conti, Cheng Peng, Zhao Yang

Description: An implementation of LUCID model (Peng (2019) <doi:10.1093/bioinformatics/btz667>).
LUCID conducts integrated clustering using exposures, omics data (and outcome
of interest). An EM algorithm is implemented to estimate MLE of LUCID model.
LUCID features integrated variable selection, incorporation of missing omics
data, bootstrap inference and visualization via Sankey diagram.
Imports: mclust, nnet, networkD3, parallel, boot, glasso, glmnet,

Imports: mclust, nnet, networkD3, boot, glasso, glmnet, jsonlite,

Imports: boot, glasso, glmnet, jsonlite, mclust, mix, networkD3, nnet,

Title: Latent Unknown Clustering Integrating Multi-View Data
person(given = "Yinqi", family = "Zhao",
person(given = "David", family = "Conti",
email = "dconti@usc.med.edu", role = "ths",
person(given = "Jesse", family = "Goodrich",
person(given = "Cheng", family = "Peng", role = "ctb")
Description: An implementation of the LUCID model (Peng (2019) <doi:10.1093/bioinformatics/btz667>).
as an option). An EM algorithm is implemented to estimate MLE of the LUCID model.
LUCIDus features integrated variable selection, incorporation of missing omics
data, bootstrap inference, prediction and visualization of the model.
Author: Yinqi Zhao [aut, cre] (<https://orcid.org/0000-0003-2413-732X>),