AdapDiscom: Adaptive Sparse Regression for Block Missing Multimodal Data

Provides adaptive direct sparse regression for high-dimensional multimodal data with heterogeneous missing patterns and measurement errors. 'AdapDISCOM' extends the 'DISCOM' framework with modality-specific adaptive weighting to handle varying data structures and error magnitudes across blocks. The method supports flexible block configurations (any K blocks) and includes robust variants for heavy-tailed distributions ('AdapDISCOM'-Huber) and fast implementations for large-scale applications (Fast-'AdapDISCOM'). Designed for realistic multimodal scenarios where different data sources exhibit distinct missing data patterns and contamination levels. Diakité et al. (2025) <doi:10.48550/arXiv.2508.00120>.

Version:	1.0.0
Depends:	R (≥ 3.5.0)
Imports:	softImpute, Matrix, scout, robustbase
Suggests:	knitr, rmarkdown, MASS
Published:	2025-08-27
DOI:	10.32614/CRAN.package.AdapDiscom
Author:	Diakite Abdoul Oudouss [aut, cre, cph], Barry Amadou [aut]
Maintainer:	Diakite Abdoul Oudouss <abdouloudoussdiakite at gmail.com>
BugReports:	https://github.com/AODiakite/AdapDiscom/issues
License:	GPL-3
URL:	https://doi.org/10.48550/arXiv.2508.00120
NeedsCompilation:	no
CRAN checks:	AdapDiscom results

Documentation:

Reference manual:	AdapDiscom.html , AdapDiscom.pdf
Vignettes:	AdapDiscom: A multimodal high dimensional method accounting for missing data and measurement error heterogeneity (source, R code)

Downloads:

Package source:	AdapDiscom_1.0.0.tar.gz
Windows binaries:	r-devel: not available, r-release: not available, r-oldrel: not available
macOS binaries:	r-release (arm64): not available, r-oldrel (arm64): not available, r-release (x86_64): AdapDiscom_1.0.0.tgz, r-oldrel (x86_64): AdapDiscom_1.0.0.tgz

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