bigMICE: Multiple Imputation of Big Data

A computational toolbox designed for handling missing values in large datasets with the Multiple Imputation by Chained Equations (MICE) by using 'Apache Spark'. The methodology is described in Morvan et al. (2026) <doi:10.48550/arXiv.2601.21613>.

Version:	1.0.0
Imports:	dplyr, tidyselect, rlang, sparklyr, data.table, Matrix
Suggests:	testthat (≥ 3.0.0), knitr, rmarkdown
Published:	2026-02-25
DOI:	10.32614/CRAN.package.bigMICE
Author:	Hugo Morvan [aut], Oleg Sysoev [aut, cre]
Maintainer:	Oleg Sysoev <oleg.sysoev at liu.se>
License:	GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation:	no
SystemRequirements:	Spark: 3.x, or 4.x
CRAN checks:	bigMICE results

Documentation:

Reference manual:	bigMICE.html , bigMICE.pdf
Vignettes:	bigMICE: multiple imputation for Big Data (source, R code)

Downloads:

Package source:	bigMICE_1.0.0.tar.gz
Windows binaries:	r-devel: bigMICE_1.0.0.zip, r-release: bigMICE_1.0.0.zip, r-oldrel: bigMICE_1.0.0.zip
macOS binaries:	r-release (arm64): bigMICE_1.0.0.tgz, r-oldrel (arm64): bigMICE_1.0.0.tgz, r-release (x86_64): bigMICE_1.0.0.tgz, r-oldrel (x86_64): bigMICE_1.0.0.tgz

Linking:

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