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Initially designed to distribute code for estimating the Gaussian graphical model with Lasso regularization, also known as the graphical lasso (glasso), using an Expectation-Maximization (EM) algorithm based on work by Städler and Bühlmann (2012) <doi:10.1007/s11222-010-9219-7>. As a byproduct, code for estimating means and covariances (or the precision matrix) under a multivariate normal (Gaussian) distribution is also available.
| Version: | 0.2.1 |
| Imports: | Rcpp, matrixcalc, Matrix, lavaan, glasso, glassoFast, caret |
| LinkingTo: | Rcpp, RcppArmadillo |
| Suggests: | testthat (≥ 3.0.0), psych, bootnet, qgraph, cglasso |
| Published: | 2024-03-04 |
| DOI: | 10.32614/CRAN.package.EMgaussian |
| Author: | Carl F. Falk [cre, aut] |
| Maintainer: | Carl F. Falk <carl.falk at mcgill.ca> |
| License: | GPL (≥ 3) |
| NeedsCompilation: | yes |
| CRAN checks: | EMgaussian results |
| Reference manual: | EMgaussian.pdf |
| Package source: | EMgaussian_0.2.1.tar.gz |
| Windows binaries: | r-devel: EMgaussian_0.2.1.zip, r-release: EMgaussian_0.2.1.zip, r-oldrel: EMgaussian_0.2.1.zip |
| macOS binaries: | r-release (arm64): EMgaussian_0.2.1.tgz, r-oldrel (arm64): EMgaussian_0.2.1.tgz, r-release (x86_64): EMgaussian_0.2.1.tgz, r-oldrel (x86_64): EMgaussian_0.2.1.tgz |
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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.