Package: misaem 1.0.1.9000

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>.

Authors:Wei Jiang [aut], Pavlo Mozharovskyi [ctb], Julie Josse [aut, cre], Imke Mayer [ctb]

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NEWS

# Install 'misaem' in R:
install.packages('misaem', repos = c('https://julierennes.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/julierennes/misaem/issues

On CRAN:

4.22 score 1 stars 33 scripts 856 downloads 8 exports 3 dependencies

Last updated 4 years agofrom:807a3261f9. Checks:OK: 7. Indexed: yes.

TargetResultDate
Doc / VignettesOKOct 27 2024
R-4.5-winOKOct 27 2024
R-4.5-linuxOKOct 27 2024
R-4.4-winOKOct 27 2024
R-4.4-macOKOct 27 2024
R-4.3-winOKOct 27 2024
R-4.3-macOKOct 27 2024

Exports:combinationslikelihood_saemlog_reglouis_lr_saemmiss.glmmiss.glm.model.selectmiss.lmmiss.lm.model.select

Dependencies:MASSmvtnormnorm

Linear regression and logistic regression with missing covariates

Wei Jiang

Rendered frommisaem.Rmdusingknitr::rmarkdownon Oct 27 2024.

Last update: 2021-04-07
Started: 2018-04-30