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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 |
| DOI: | 10.32614/CRAN.package.latentgraph |
| Author: | Yanxin Jin, Samantha Yang, Kean Ming Tan |
| Maintainer: | Yanxin Jin <yanxinj at umich.edu> |
| License: | GPL-3 |
| NeedsCompilation: | yes |
| CRAN checks: | latentgraph results |
| Reference manual: | latentgraph.pdf |
| 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 |
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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.