Sparse regression for related problems

Estimates sparse regression models (i.e., with few non-zero coefficients) in high-dimensional multi-task learning and transfer learning settings

Installation

Install the current release from CRAN:

r install.packages("sparselink")

or the latest development version from GitHub:

``` r

install.packages("remotes")

remotes::install_github("rauschenberger/sparselink") ```

This repository is mirrored on two institutional GitLab instances (see LIH and LCSB).

Reference

Armin Rauschenberger , Petr V. Nazarov , and Enrico Glaab (2025). "Estimating sparse regression models in multi-task learning and transfer learning through adaptive penalisation". Bioinformatics. doi: 10.1093/bioinformatics/btaf406

Reproducibility

The code for reproducing the simulations and applications shown in the manuscript is available in a vignette (analysis). After installing the package with remotes::install_github("rauschenberger/sparselink",build_vignettes=TRUE) and restarting R, the vignette can also be loaded with vignette(topic="analysis",package="sparselink").

Disclaimer

The R package sparselink implements sparse regression for related problems (Rauschenberger et al., 2025).

Copyright © 2025 Armin Rauschenberger; Luxembourg Institute of Health (LIH), Department of Medical Informatics (DMI), Bioinformatics and Artificial Intelligence (BioAI); University of Luxembourg, Luxembourg Centre for Systems Biomedicine (LCSB), Biomedical Data Science (BDS)

Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.

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