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.

Version: 0.1.5
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: 2021-03-23
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
CRAN checks: gerbil results

Downloads:

Reference manual: gerbil.pdf
Vignettes: Gerbil Introduction
Package source: gerbil_0.1.5.tar.gz
Windows binaries: r-devel: gerbil_0.1.5.zip, r-release: gerbil_0.1.5.zip, r-oldrel: gerbil_0.1.5.zip
macOS binaries: r-release: gerbil_0.1.5.tgz, r-oldrel: gerbil_0.1.5.tgz

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