misaem: Linear Regression and Logistic Regression with Missing Covariates

Estimate parameters of linear regression and logistic regression with missing covariates with missing data, perform model selection and prediction, using EM-type algorithms. Jiang W., Josse J., Lavielle M., TraumaBase Group (2020) <doi:10.1016/j.csda.2019.106907>.

Version:	1.1.0
Depends:	R (≥ 3.4.0)
Imports:	mvtnorm, stats, MASS, norm, methods, abind, glmnet
Suggests:	knitr, rmarkdown, mice
Published:	2025-09-11
DOI:	10.32614/CRAN.package.misaem
Author:	Wei Jiang [aut], Pavlo Mozharovskyi [ctb], Imke Mayer [ctb], Christophe Muller [ctb], Julie Josse [aut, cre]
Maintainer:	Julie Josse <julie.josse at inria.fr>
BugReports:	https://github.com/julierennes/misaem/issues
License:	GPL-3
URL:	https://github.com/julierennes/misaem
NeedsCompilation:	no
Citation:	misaem citation info
Materials:	README, NEWS
In views:	MissingData
CRAN checks:	misaem results

Documentation:

Reference manual:	misaem.html , misaem.pdf
Vignettes:	Linear regression and logistic regression with missing covariates (source, R code)

Downloads:

Package source:	misaem_1.1.0.tar.gz
Windows binaries:	r-devel: misaem_1.1.0.zip, r-release: misaem_1.1.0.zip, r-oldrel: misaem_1.1.0.zip
macOS binaries:	r-release (arm64): misaem_1.1.0.tgz, r-oldrel (arm64): misaem_1.1.0.tgz, r-release (x86_64): misaem_1.1.0.tgz, r-oldrel (x86_64): misaem_1.1.0.tgz
Old sources:	misaem archive

Reverse dependencies:

Reverse suggests:

WeightIt

Linking:

Please use the canonical form https://CRAN.R-project.org/package=misaem to link to this page.