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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 |
DOI: | 10.32614/CRAN.package.gerbil |
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 |
Reference manual: | gerbil.pdf |
Vignettes: |
Gerbil Introduction |
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, r-oldrel (x86_64): gerbil_0.1.9.tgz |
Old sources: | gerbil archive |
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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.