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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) <arXiv:2008.02243>.
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Package details |
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| Author | Michael Robbins [aut, cre], Max Griswold [ctb], Pedro Nascimento de Lima [ctb] |
| Maintainer | Michael Robbins <mrobbins@rand.org> |
| License | GPL-2 |
| Version | 0.1.9 |
| Package repository | View on CRAN |
| Installation |
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