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: 1.0.1
Depends: R (≥ 3.4.0)
Imports: mvtnorm, stats, MASS, norm, methods
Suggests: knitr, rmarkdown, mice
Published: 2021-04-12
DOI: 10.32614/CRAN.package.misaem
Author: Wei Jiang [aut], Pavlo Mozharovskyi [ctb], Julie Josse [aut, cre], Imke Mayer [ctb]
Maintainer: Julie Josse <julie.josserennes at gmail.com>
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


Reference manual: misaem.pdf
Vignettes: Linear regression and logistic regression with missing covariates


Package source: misaem_1.0.1.tar.gz
Windows binaries: r-devel: misaem_1.0.1.zip, r-release: misaem_1.0.1.zip, r-oldrel: misaem_1.0.1.zip
macOS binaries: r-release (arm64): misaem_1.0.1.tgz, r-oldrel (arm64): misaem_1.0.1.tgz, r-release (x86_64): misaem_1.0.1.tgz, r-oldrel (x86_64): misaem_1.0.1.tgz
Old sources: misaem archive

Reverse dependencies:

Reverse suggests: WeightIt


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