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latentgraph: Graphical Models with Latent Variables

Three methods are provided to estimate graphical models with latent variables: (1) Jin, Y., Ning, Y., and Tan, K. M. (2020) (preprint available); (2) Chandrasekaran, V., Parrilo, P. A. & Willsky, A. S. (2012) <doi:10.1214/11-AOS949>; (3) Tan, K. M., Ning, Y., Witten, D. M. & Liu, H. (2016) <doi:10.1093/biomet/asw050>.

Version: 1.1
Imports: Rcpp, pracma, glmnet, MASS, stats
LinkingTo: Rcpp, RcppArmadillo
Published: 2020-12-10
Author: Yanxin Jin, Samantha Yang, Kean Ming Tan
Maintainer: Yanxin Jin <yanxinj at umich.edu>
License: GPL-3
NeedsCompilation: yes
CRAN checks: latentgraph results

Documentation:

Reference manual: latentgraph.pdf

Downloads:

Package source: latentgraph_1.1.tar.gz
Windows binaries: r-devel: latentgraph_1.1.zip, r-release: latentgraph_1.1.zip, r-oldrel: latentgraph_1.1.zip
macOS binaries: r-release (arm64): latentgraph_1.1.tgz, r-oldrel (arm64): latentgraph_1.1.tgz, r-release (x86_64): latentgraph_1.1.tgz, r-oldrel (x86_64): latentgraph_1.1.tgz
Old sources: latentgraph archive

Linking:

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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.
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