em: Generic EM Algorithm

A generic function for running the Expectation-Maximization (EM) algorithm within a maximum likelihood framework, based on Dempster, Laird, and Rubin (1977) <doi:10.1111/j.2517-6161.1977.tb01600.x> is implemented. It can be applied after a model fitting using R's existing functions and packages.

Version: 1.0.0
Depends: R (≥ 3.0.0)
Imports: stats, utils, survival, plm, methods, mclust, dplyr, numDeriv, nnet, magrittr
LinkingTo: Rcpp, RcppArmadillo
Suggests: testthat (≥ 3.0.0), parallel, fitdistrplus, gnm
Published: 2023-01-11
Author: Dongjie Wu ORCID iD [aut, cre, cph]
Maintainer: Dongjie Wu <dwu.jacob at gmail.com>
BugReports: https://github.com/wudongjie/em/issues
License: GPL (≥ 3)
URL: https://github.com/wudongjie/em
NeedsCompilation: yes
SystemRequirements: C++11
CRAN checks: em results

Documentation:

Reference manual: em.pdf
Vignettes: em: A Generic Function of the EM Algorithm for Finite Mixture Models in R

Downloads:

Package source: em_1.0.0.tar.gz
Windows binaries: r-devel: em_1.0.0.zip, r-release: em_1.0.0.zip, r-oldrel: em_1.0.0.zip
macOS binaries: r-release (arm64): em_1.0.0.tgz, r-oldrel (arm64): em_1.0.0.tgz, r-release (x86_64): em_1.0.0.tgz

Linking:

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