gerbil: Generalized Efficient Regression-Based Imputation with Latent Processes

Implements a new multiple imputation method that draws imputations from a latent joint multivariate normal model which underpins generally structured data. This model is constructed using a sequence of flexible conditional linear models that enables the resulting procedure to be efficiently implemented on high dimensional datasets in practice. See Robbins (2021) <doi:10.48550/arXiv.2008.02243>.

Version: 0.1.9
Depends: R (≥ 2.10)
Imports: base, DescTools, graphics, grDevices, lattice, MASS, mvtnorm, openxlsx, parallel, pbapply, stats, truncnorm, utils
Suggests: dplyr, knitr, mice, rmarkdown, testthat (≥ 2.1.0)
Published: 2023-01-12
Author: Michael Robbins [aut, cre], Max Griswold [ctb], Pedro Nascimento de Lima [ctb]
Maintainer: Michael Robbins <mrobbins at rand.org>
License: GPL-2
NeedsCompilation: no
Materials: README NEWS
In views: MissingData
CRAN checks: gerbil results

Documentation:

Reference manual: gerbil.pdf
Vignettes: Gerbil Introduction

Downloads:

Package source: gerbil_0.1.9.tar.gz
Windows binaries: r-devel: gerbil_0.1.9.zip, r-release: gerbil_0.1.9.zip, r-oldrel: gerbil_0.1.9.zip
macOS binaries: r-release (arm64): gerbil_0.1.9.tgz, r-oldrel (arm64): gerbil_0.1.9.tgz, r-release (x86_64): gerbil_0.1.9.tgz
Old sources: gerbil archive

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