Main Effects and Interactions in Mixed and Incomplete Data

Estimation of main effects and interactions in mixed data sets with missing values. Numeric, binary and count variables are supported. Main effects and interactions are modelled using an exponential family parametric model. Particular examples include the log-linear model for count data and the linear model for numeric data. Estimation is done through a convex program where main effects are assumed sparse and the interactions low-rank. Geneviève Robin, Olga Klopp, Julie Josse, Éric Moulines, Robert Tibshirani (2018) .


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install.packages("mimi")

0.1.0 by Genevieve Robin, a month ago


Browse source code at https://github.com/cran/mimi


Authors: Geneviève Robin


Documentation:   PDF Manual  


Task views: Missing Data


GPL-3 license


Imports glmnet, softImpute, stats, ade4, FactoMineR, parallel, doParallel, foreach, data.table

Suggests knitr, rmarkdown


See at CRAN