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rCISSVAE: Clustering-Informed Shared-Structure VAE for Imputation

Implements the Clustering-Informed Shared-Structure Variational Autoencoder ('CISS-VAE'), a deep learning framework for missing data imputation introduced in Khadem Charvadeh et al. (2025) <doi:10.1002/sim.70335>. The model accommodates all three types of missing data mechanisms: Missing Completely At Random (MCAR), Missing At Random (MAR), and Missing Not At Random (MNAR). While it is particularly well-suited to MNAR scenarios, where missingness patterns carry informative signals, 'CISS-VAE' also functions effectively under MAR assumptions.

Version: 0.0.4
Depends: R (≥ 4.2.0)
Imports: reticulate, purrr, gtsummary, rlang, ComplexHeatmap
Suggests: testthat (≥ 3.0.0), dplyr, knitr, rmarkdown, tidyverse, kableExtra, MASS, fastDummies, palmerpenguins, glue, withr, ggplot2
Published: 2026-01-23
DOI: 10.32614/CRAN.package.rCISSVAE
Author: Yasin Khadem Charvadeh [aut], Kenneth Seier [aut], Katherine S. Panageas [aut], Danielle Vaithilingam [aut, cre], Mithat Gönen [aut], Yuan Chen [aut]
Maintainer: Danielle Vaithilingam <vaithid1 at mskcc.org>
BugReports: https://github.com/CISS-VAE/rCISS-VAE/issues
License: MIT + file LICENSE
URL: https://ciss-vae.github.io/rCISS-VAE/
NeedsCompilation: no
CRAN checks: rCISSVAE results

Documentation:

Reference manual: rCISSVAE.html , rCISSVAE.pdf
Vignettes: Handling Binary and Categorical Variables (source, R code)
'Masking certain entries from imputation model' (source, R code)
"Saving and Using Saved Models" (source, R code)
Using Optuna Dashboard with rCISSVAE (source, R code)
Summary Functions (source, R code)
rCISSVAE Vignette (source, R code)
Manual Virtual Environment Setup Tutorial (source, R code)

Downloads:

Package source: rCISSVAE_0.0.4.tar.gz
Windows binaries: r-devel: rCISSVAE_0.0.4.zip, r-release: rCISSVAE_0.0.4.zip, r-oldrel: not available
macOS binaries: r-release (arm64): rCISSVAE_0.0.4.tgz, r-oldrel (arm64): rCISSVAE_0.0.4.tgz, r-release (x86_64): rCISSVAE_0.0.4.tgz, r-oldrel (x86_64): rCISSVAE_0.0.4.tgz

Linking:

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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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