Package: AdapDiscom
Type: Package
Title: Adaptive Sparse Regression for Block Missing Multimodal Data
Version: 1.0.0
Date: 2025-08-18
Authors@R: c(
    person("Diakite", "Abdoul Oudouss", email = "abdouloudoussdiakite@gmail.com", role = c("aut","cre","cph")),
    person("Barry","Amadou", email = "amadoudiogo.barry@inrs.ca", role = "aut"))
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>.
License: GPL-3
URL: https://doi.org/10.48550/arXiv.2508.00120
BugReports: https://github.com/AODiakite/AdapDiscom/issues
Depends: R (>= 3.5.0)
Imports: softImpute, Matrix, scout, robustbase
RoxygenNote: 7.3.2
Encoding: UTF-8
Suggests: knitr, rmarkdown, MASS
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2025-08-22 03:44:24 UTC; abdoul
Author: Diakite Abdoul Oudouss [aut, cre, cph],
  Barry Amadou [aut]
Maintainer: Diakite Abdoul Oudouss <abdouloudoussdiakite@gmail.com>
Repository: CRAN
Date/Publication: 2025-08-27 16:30:27 UTC
Built: R 4.6.0; ; 2026-04-27 13:52:49 UTC; unix
