CRAN/E | rMIDAS

rMIDAS

Multiple Imputation with Denoising Autoencoders

Installation

About

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.

Citation rMIDAS citation info
github.com/MIDASverse/rMIDAS
System requirements Python (>= 3.6.0)
Bug report File report

Key Metrics

Version 1.0.0
R ≥ 3.6.0
Published 2023-10-11 205 days ago
Needs compilation? no
License Apache License (≥ 2.0)
CRAN checks rMIDAS results

Downloads

Yesterday 25 0%
Last 7 days 79 -30%
Last 30 days 350 +4%
Last 90 days 942 -33%
Last 365 days 4.789 +25%

Maintainer

Maintainer

Thomas Robinson

ts.robinson1994@gmail.com

Authors

Thomas Robinson

aut / cre / cph

Ranjit Lall

aut / cph

Alex Stenlake

ctb / cph

Elviss Dvinskis

ctb

Material

README
NEWS
Reference manual
Package source

In Views

MissingData

Vignettes

Using custom Python versions
Imputing missing data using rMIDAS
Running rMIDAS on a server instance

macOS

r-release

arm64

r-oldrel

arm64

r-release

x86_64

r-oldrel

x86_64

Windows

r-devel

x86_64

r-release

x86_64

r-oldrel

x86_64

Old Sources

rMIDAS archive

Depends

R ≥ 3.6.0
data.table
mltools
reticulate

Imports

rappdirs
Rdpack

Suggests

testthat
knitr
rmarkdown