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.
| Version: | 1.0.0 |
| Depends: | R (≥ 4.1.0) |
| Imports: | dplyr (≥ 1.1.0), future.apply (≥ 1.11.0), parsnip (≥ 1.2.0), recipes (≥ 1.0.0), rsample (≥ 1.2.0), stacks (≥ 1.0.0), stats, tibble (≥ 3.2.0), tidyr (≥ 1.3.0), tune (≥ 1.2.0), utils, workflows (≥ 1.1.0) |
| Suggests: | earth (≥ 5.3.0), future (≥ 1.33.0), knitr, ranger (≥ 0.16.0), rmarkdown, testthat (≥ 3.0.0), xgboost (≥ 1.7.0) |
| Published: | 2026-03-30 |
| DOI: | 10.32614/CRAN.package.misl |
| Author: | Justin Manjourides [aut, cre] |
| Maintainer: | Justin Manjourides <j.manjourides at northeastern.edu> |
| BugReports: | https://github.com/JustinManjourides/misl/issues |
| License: | MIT + file LICENSE |
| URL: | https://github.com/JustinManjourides/misl |
| NeedsCompilation: | no |
| Materials: | README, NEWS |
| CRAN checks: | misl results |
| Reference manual: | misl.html , misl.pdf |
| Vignettes: |
Introduction to misl (source, R code) |
| Package source: | misl_1.0.0.tar.gz |
| Windows binaries: | r-devel: misl_1.0.0.zip, r-release: misl_1.0.0.zip, r-oldrel: not available |
| macOS binaries: | r-release (arm64): misl_1.0.0.tgz, r-oldrel (arm64): not available, r-release (x86_64): misl_1.0.0.tgz, r-oldrel (x86_64): misl_1.0.0.tgz |
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