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AdapDiscom  

Adaptive Sparse Regression for Block Missing Multimodal Data
View on CRAN: Click here


Download and install AdapDiscom package within the R console
Install from CRAN:
install.packages("AdapDiscom")

Install from Github:
library("remotes")
install_github("cran/AdapDiscom")

Install by package version:
library("remotes")
install_version("AdapDiscom", "1.0.0")



Attach the package and use:
library("AdapDiscom")
Maintained by
Diakite Abdoul Oudouss
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2025-08-27
Latest Update: 2025-08-27
Description:
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>.
How to cite:
Diakite Abdoul Oudouss (2025). AdapDiscom: Adaptive Sparse Regression for Block Missing Multimodal Data. R package version 1.0.0, https://cran.r-project.org/web/packages/AdapDiscom. Accessed 24 Oct. 2026.
Previous versions and publish date:
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Complete documentation for AdapDiscom
Functions, R codes and Examples using the AdapDiscom R package
Full AdapDiscom package functions and examples
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