misl: Multiple Imputation by Super Learning

Performs multiple imputation of missing data using an ensemble super learner built with the tidymodels framework. For each incomplete column, a stacked ensemble of candidate learners is trained on a bootstrap sample of the observed data and used to generate imputations via predictive mean matching (continuous), probability draws (binary), or cumulative probability draws (categorical). Supports parallelism across imputed datasets via the future framework.

Package details

AuthorJustin Manjourides [aut, cre] (ORCID: <https://orcid.org/0000-0002-2454-4489>), Thomas Carpenito [aut] (ORCID: <https://orcid.org/0000-0003-3591-0680>)
MaintainerJustin Manjourides <j.manjourides@northeastern.edu>
LicenseMIT + file LICENSE
Version2.0.0
URL https://github.com/JustinManjourides/misl
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:
install.packages("misl")

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misl documentation built on April 8, 2026, 9:07 a.m.