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rMIDAS2: Multiple Imputation with 'MIDAS2' Denoising Autoencoders
Fits 'MIDAS' denoising autoencoder models for multiple imputation of missing data, generates multiply-imputed datasets, computes imputation means, and runs Rubin's rules regression analysis. Wraps the 'MIDAS2' 'Python' engine via a local 'FastAPI' server over 'HTTP', so no 'reticulate' dependency is needed at runtime. Methods are described in Lall and Robinson (2022) <doi:10.1017/pan.2020.49> and Lall and Robinson (2023) <doi:10.18637/jss.v107.i09>.
Getting started
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Package details |
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| Author | Thomas Robinson [aut, cre], Ranjit Lall [aut] |
| Maintainer | Thomas Robinson <t.robinson7@lse.ac.uk> |
| License | MIT + file LICENSE |
| Version | 0.1.1 |
| URL | https://github.com/MIDASverse/MIDAS2 |
| Package repository | View on CRAN |
| Installation |
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