[aut, cre, cph],
Ranjit Lall [aut,
cph],
Alex Stenlake [ctb, cph]A tool that allows users to impute missing data with 'MIDAS', a multiple imputation method using denoising autoencoders as documented in Lall and Robinson (2020) <doi:10.33774/apsa-2020-3tk40-v3>. This method has significant accuracy and efficiency advantages over other multiple imputation strategies, particularly when run on large datasets with many columns or categories. Alongside interfacing with 'Python' to run the core algorithm, this package contains tools to process the data before and after model training, run imputation model diagnostics, generate multiple completed datasets, and estimate multiply-imputed regression models.
| Version: | 0.1.0 |
| Depends: | R (≥ 3.6.0), data.table, mltools, reticulate |
| Suggests: | testthat |
| Published: | 2020-09-29 |
| Author: | Thomas Robinson
[aut, cre, cph],
Ranjit Lall [aut,
cph],
Alex Stenlake [ctb, cph] |
| Maintainer: | Thomas Robinson <ts.robinson1994 at gmail.com> |
| BugReports: | https://github.com/MIDASverse/rMIDAS/issues |
| License: | Apache License (≥ 2.0) |
| URL: | https://github.com/MIDASverse/rMIDAS |
| NeedsCompilation: | no |
| Citation: | rMIDAS citation info |
| Materials: | README NEWS |
| CRAN checks: | rMIDAS results |
| Reference manual: | rMIDAS.pdf |
| Package source: | rMIDAS_0.1.0.tar.gz |
| Windows binaries: | r-devel: rMIDAS_0.1.0.zip, r-release: rMIDAS_0.1.0.zip, r-oldrel: rMIDAS_0.1.0.zip |
| macOS binaries: | r-release: rMIDAS_0.1.0.tgz, r-oldrel: rMIDAS_0.1.0.tgz |
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