rMIDAS
1.0.1Multiple Imputation with Denoising Autoencoders
Overview
A tool for multiply imputing missing data using 'MIDAS', a deep learning method based on denoising autoencoder neural networks (see Lall and Robinson, 2022; doi:10.1017/pan.2020.49). This algorithm offers significant accuracy and efficiency advantages over other multiple imputation strategies, particularly when applied to large datasets with complex features. Alongside interfacing with 'Python' to run the core algorithm, this package contains functions for processing data before and after model training, running imputation model diagnostics, generating multiple completed datasets, and estimating regression models on these datasets. For more information see Lall and Robinson (2023) doi:10.18637/jss.v107.i09. This package is deprecated in favor of 'rMIDAS2'; it remains available for existing workflows but will receive only compatibility and documentation updates.
Install
Health
- OK2026-03-1014 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
Documentation
- Examples that run
- 90%
- Documented parameters
- 95%
- Return-value docs
- 93%
- References docs
- 19%
Downloads
Repository
Repository practices
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Checks run against github.com/midasverse/rmidas on 2026-07-19.
Dependencies
Nothing depends on this yet.
Code & Tests
People & History
9 releases. Pick two to compare their code metrics. R releases are shown for context.
- RR 4.6.0 released · 2026-04-24
- 1.0.1Latest
- RR 4.5.0 released · 2025-04-11
- RR 4.4.0 released · 2024-04-24
- 1.0.02023-10-11 · diff ↗
- 0.5.02023-08-23 · diff ↗
- 0.4.22023-06-14 · diff ↗
- RR 4.3.0 released · 2023-04-21
- 0.4.12022-06-20 · diff ↗
- RR 4.2.0 released · 2022-04-22
- 0.4.02022-02-10 · diff ↗
- RR 4.1.0 released · 2021-05-18
- 0.3.02021-01-30 · diff ↗
- 0.2.02020-11-02 · diff ↗
- 0.1.02020-09-29
- RR 4.0.0 released · 2020-04-24
Package metadata
- First published
- 2020-09-29
- Total releases
- 9 / 6 yrs
- License
- Apache License (>= 2.0)
- Minimum R
- ≥ 3.6.0
- Download size
- 192 KB
- Installed size
- not tracked yet
- With dependencies
- not tracked yet