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 |