Expectation-Maximization Algorithm for Multivariate Normal (Gaussian) with Missing Data R package EMgaussian version 0.2.2 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. Software Imports: Rcpp, matrixcalc, Matrix, lavaan, glasso, glassoFast, caret LinkingTo: Rcpp, RcppArmadillo Suggests: testthat (>= 3.0.0), psych, bootnet, qgraph, cglasso Carl F. Falk <carl.falk@mcgill.ca> Comprehensive R Archive Network (CRAN) Carl F. Falk [cre, aut] GPL (>= 3) 2025-07-24 application/tgz https://CRAN.R-project.org/package=EMgaussian doi:10.32614/CRAN.package.EMgaussian