Package: EMgaussian 0.2.1

Carl F. Falk

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.

Authors:Carl F. Falk [cre, aut]

EMgaussian_0.2.1.tar.gz
EMgaussian_0.2.1.tar.gz(r-4.5-noble)EMgaussian_0.2.1.tar.gz(r-4.4-noble)
EMgaussian_0.2.1.tgz(r-4.4-emscripten)EMgaussian_0.2.1.tgz(r-4.3-emscripten)
EMgaussian.pdf |EMgaussian.html✨
EMgaussian/json (API)

# Install 'EMgaussian' in R:
install.packages('EMgaussian', repos = 'https://cloud.r-project.org')
Uses libs:
  • openblas– Optimized BLAS
  • c++– GNU Standard C++ Library v3

On CRAN:

Conda:

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

openblascpp

1.00 score 478 downloads 5 exports 84 dependencies

Last updated 1 years agofrom:eb506d204d. Checks:2 OK, 1 NOTE. Indexed: no.

TargetResultLatest binary
Doc / VignettesOKMar 30 2025
R-4.5-linux-x86_64NOTEMar 30 2025
R-4.4-linux-x86_64OKMar 30 2025

Exports:em.covem.precEMggmrhogridstartvals.cov

Dependencies:caretclasscliclockcodetoolscolorspacecpp11data.tablediagramdigestdplyre1071fansifarverforeachfuturefuture.applygenericsggplot2glassoglassoFastglobalsgluegowergtablehardhatipredisobanditeratorsKernSmoothlabelinglatticelavalavaanlifecyclelistenvlubridatemagrittrMASSMatrixmatrixcalcmgcvmnormtModelMetricsmunsellnlmennetnumDerivparallellypbivnormpillarpkgconfigplyrpROCprodlimprogressrproxypurrrquadprogR6RColorBrewerRcppRcppArmadillorecipesreshape2rlangrpartscalesshapesparsevctrsSQUAREMstringistringrsurvivaltibbletidyrtidyselecttimechangetimeDatetzdbutf8vctrsviridisLitewithr

Citation

To cite package ‘EMgaussian’ in publications use:

Falk CF (2024). EMgaussian: Expectation-Maximization Algorithm for Multivariate Normal (Gaussian) with Missing Data. R package version 0.2.1, https://CRAN.R-project.org/package=EMgaussian.

Corresponding BibTeX entry: 

  @Manual{,
    title = {EMgaussian: Expectation-Maximization Algorithm for
      Multivariate Normal (Gaussian) with Missing Data},
    author = {Carl F. Falk},
    year = {2024},
    note = {R package version 0.2.1},
    url = {https://CRAN.R-project.org/package=EMgaussian},
  }