Package: rMIDAS 0.5.0

Thomas Robinson

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. 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.

Authors:Thomas Robinson [aut, cre, cph], Ranjit Lall [aut, cph], Alex Stenlake [ctb, cph], Elviss Dvinskis [ctb]

rMIDAS_0.5.0.tar.gz
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rMIDAS.pdf |rMIDAS.html✨
rMIDAS/json (API)
NEWS

Peer review:

Bug tracker:https://github.com/midasverse/rmidas/issues

On CRAN:

deep-learningimputation-methodsneural-networkreticulatetensorflow

14 exports 30 stars 2.54 score 14 dependencies 32 scripts 315 downloads

Last updated 11 months agofrom:a53fddfed2. Checks:OK: 7. Indexed: yes.

Exports:add_bin_labelsadd_missingnesscol_minmaxcombinecompleteconvertdelete_rMIDAS_envmidas_setupna_to_nanoverimputereset_rMIDAS_envset_python_envtrainundo_minmax

Dependencies:data.tableherejsonlitelatticeMatrixmltoolspngrappdirsRcppRcppTOMLreticulaterlangrprojrootwithr