misl

cranv2.0.0

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 (

License MIT + file LICENSE0 versions1 maintainers12 deps137 weekly dl
JustinManjourides/misl
55
/ 100
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safe to use

[email protected] is safe to use (health: 55/100)

Health breakdown0 – 100
25/25
maintenance
3/20
popularity
25/25
security
0/15
maturity
2/15
community
Vulnerabilities
0
none known
⚠ Possible typosquat
Name is close to a popular package. Targets:
mime (adjacent_swap_or_double dist 2)MASS (adjacent_swap_or_double dist 2)mice (adjacent_swap_or_double dist 2)

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Dependencies (12)
dplyrfuture.applyparsniprecipesrsamplestacksstatstibbletidyrtuneutilsworkflows
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First published · 2026-04-08 05:30:49

Last updated · 2026-04-08T04:00:02+00:00