Skip to content

misl

Multiple Imputation by Super Learning

v2.0.0 · Apr 7, 2026 · MIT + file LICENSE

Description

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.

Downloads

CRAN

435

Last 30 days

9168th

1.4K

Last 90 days

1.4K

Last year

Trend: -7.1% (30d vs prior 30d)

r2u CRAN

7

Last 30 days

30

Last 90 days

30

Last year

Trend: -69.6% (30d vs prior 30d)

autoCRAN

0

Last 7 days

1

Last 30 days

0

All-time

autoCRAN-only: this name is served only by autoCRAN, so the count is exact.

CRAN Check Status

13 OK
Show all 13 flavors
Flavor Status
r-devel-linux-x86_64-debian-clang OK
r-devel-linux-x86_64-debian-gcc OK
r-devel-linux-x86_64-fedora-clang OK
r-devel-linux-x86_64-fedora-gcc OK
r-devel-windows-x86_64 OK
r-oldrel-macos-arm64 OK
r-oldrel-macos-x86_64 OK
r-oldrel-windows-x86_64 OK
r-patched-linux-x86_64 OK
r-release-linux-x86_64 OK
r-release-macos-arm64 OK
r-release-macos-x86_64 OK
r-release-windows-x86_64 OK

Check History

OK 13 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE Jun 9, 2026
ERROR 12 OK · 0 NOTE · 0 WARNING · 1 ERROR · 0 FAILURE Jun 8, 2026
ERROR r-devel-linux-x86_64-debian-gcc

package dependencies

Packages required but not available:
  'parsnip', 'recipes', 'rsample', 'stacks', 'tune', 'workflows'

See section ‘The DESCRIPTION file’ in the ‘Writing R Extensions’
manual.
OK 7 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE Mar 31, 2026

Dependency Network

Dependencies Reverse dependencies dplyr future.apply parsnip (>= 1.2.0) recipes rsample stacks (>= 1.0.0) tibble tidyr tune (>= 1.2.0) workflows misl

Version History

2 tracked
updated 2.0.0 ← 1.0.0 diff Apr 8, 2026
new 1.0.0 Mar 30, 2026