rMIDAS
Multiple Imputation with Denoising Autoencoders
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.
- Version1.0.0
- R version≥ 3.6.0
- LicenseApache License (≥ 2.0)
- Needs compilation?No
- rMIDAS citation info
- Last release10/11/2023
Documentation
Team
Thomas Robinson
Ranjit Lall
Alex Stenlake
Show author detailsRolesContributor, Copyright holderElviss Dvinskis
Show author detailsRolesContributor
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