Adaptive Sparse Regression for Block Missing Multimodal Data R package AdapDiscom version 1.0.0 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>. Software Depends: R (>= 3.5.0) Imports: softImpute, Matrix, scout, robustbase Suggests: knitr, rmarkdown, MASS Diakite Abdoul Oudouss <abdouloudoussdiakite@gmail.com> Comprehensive R Archive Network (CRAN) Diakite Abdoul Oudouss [aut, cre, cph], Barry Amadou [aut] GPL-3 2025-08-27 application/tgz https://CRAN.R-project.org/package=AdapDiscom doi:10.32614/CRAN.package.AdapDiscom