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>.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
0.1.1 |
rolling linux/jammy R-4.5 | rMIDAS2_0.1.1.tar.gz |
90.9 KiB |
0.1.1 |
rolling linux/noble R-4.5 | rMIDAS2_0.1.1.tar.gz |
90.4 KiB |
0.1.1 |
rolling source/ R- | rMIDAS2_0.1.1.tar.gz |
22.7 KiB |
0.1.1 |
latest linux/jammy R-4.5 | rMIDAS2_0.1.1.tar.gz |
90.9 KiB |
0.1.1 |
latest linux/noble R-4.5 | rMIDAS2_0.1.1.tar.gz |
90.4 KiB |
0.1.1 |
latest source/ R- | rMIDAS2_0.1.1.tar.gz |
22.7 KiB |
0.1.1 |
2026-04-26 source/ R- | rMIDAS2_0.1.1.tar.gz |
22.7 KiB |
0.1.1 |
2026-04-23 source/ R- | rMIDAS2_0.1.1.tar.gz |
22.7 KiB |
0.1.1 |
2026-04-09 windows/windows R-4.5 | rMIDAS2_0.1.1.zip |
94.6 KiB |