Package: latentgraph 1.1

Yanxin Jin

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>.

Authors:Yanxin Jin, Samantha Yang, Kean Ming Tan

latentgraph_1.1.tar.gz
latentgraph_1.1.tar.gz(r-4.5-noble)latentgraph_1.1.tar.gz(r-4.4-noble)
latentgraph_1.1.tgz(r-4.4-emscripten)latentgraph_1.1.tgz(r-4.3-emscripten)
latentgraph.pdf |latentgraph.html
latentgraph/json (API)

# Install 'latentgraph' in R:
install.packages('latentgraph', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Uses libs:
  • openblas– Optimized BLAS
  • c++– GNU Standard C++ Library v3

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

openblascpp

1.00 score 135 downloads 4 exports 13 dependencies

Last updated 4 years agofrom:f7fe7ed9b6. Checks:OK: 1 NOTE: 1. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 28 2024
R-4.5-linux-x86_64NOTENov 28 2024

Exports:corlatentgenerate_Gaussianlvglassosemilatent

Dependencies:codetoolsforeachglmnetiteratorslatticeMASSMatrixpracmaRcppRcppArmadilloRcppEigenshapesurvival