This package is considered a duplicate. The official version of this package is found at:https://falkcarl.r-universe.dev/EMgaussian

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 = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

Uses libs:

openblas– Optimized BLAS
c++– GNU Standard C++ Library v3

On CRAN:

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

openblas cpp

1.00 score 632 downloads 5 exports 84 dependencies

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

Target	Result	Latest binary
Doc / Vignettes	OK	Feb 28 2025
R-4.5-linux-x86_64	NOTE	Feb 28 2025

Exports:em.cov em.prec EMggm rhogrid startvals.cov

Dependencies:caret class cli clock codetools colorspace cpp11 data.table diagram digest dplyr e1071 fansi farver foreach future future.apply generics ggplot2 glasso glassoFast globals glue gower gtable hardhat ipred isoband iterators KernSmooth labeling lattice lava lavaan lifecycle listenv lubridate magrittr MASS Matrix matrixcalc mgcv mnormt ModelMetrics munsell nlme nnet numDeriv parallelly pbivnorm pillar pkgconfig plyr pROC prodlim progressr proxy purrr quadprog R6 RColorBrewer Rcpp RcppArmadillo recipes reshape2 rlang rpart scales shape sparsevctrs SQUAREM stringi stringr survival tibble tidyr tidyselect timechange timeDate tzdb utf8 vctrs viridisLite withr

Help page	Topics
EM algorithm for multivariate normal, covariance matrix parameterization	em.cov
EM algorithm for multivariate normal, precision matrix parameterization	em.prec
Regularized GGM under missing data with EBIC or k-fold cross validation	EMggm
Create sequence of possible tuning parameter values	rhogrid
Starting values for means and covariances	startvals.cov

Package: EMgaussian 0.2.1

EMgaussian: Expectation-Maximization Algorithm for Multivariate Normal (Gaussian) with Missing Data

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Help Manual

Usage by other packages (reverse dependencies)