EMgaussian
Expectation-Maximization Algorithm for Multivariate Normal (Gaussian) with Missing Data
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.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
0.2.2 |
rolling source/ R- | EMgaussian_0.2.2.tar.gz |
36.8 KiB |
0.2.2 |
latest source/ R- | EMgaussian_0.2.2.tar.gz |
36.8 KiB |
0.2.2 |
2026-04-09 windows/windows R-4.5 | EMgaussian_0.2.2.zip |
445.0 KiB |