https://github.com/rauschenberger/corila

Sparse modelling with grouped and correlated features
https://github.com/rauschenberger/corila

correlated-features group-lasso information-exchange privileged-information sparsity

Last synced: 28 days ago
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Sparse modelling with grouped and correlated features

• Host: GitHub
• URL: https://github.com/rauschenberger/corila
• Owner: rauschenberger
• License: gpl-3.0
• Created: 2025-09-24T07:38:05.000Z (10 months ago)
• Default Branch: main
• Last Pushed: 2026-06-18T15:08:02.000Z (about 1 month ago)
• Last Synced: 2026-06-18T15:18:20.822Z (about 1 month ago)
• Topics: correlated-features, group-lasso, information-exchange, privileged-information, sparsity
• Language: R
• Homepage: https://rauschenberger.github.io/corila/
• Size: 1.87 MB
• Stars: 0
• Watchers: 0
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • Changelog: NEWS.md
  • Contributing: CONTRIBUTING.md
  • License: LICENSE.md
  • Citation: CITATION.cff

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# Sparse modelling with grouped and correlated features

## Scope

The R package `corila` implements sparse modelling with grouped and correlated features allowing for privileged information (_Rauschenberger_, 2026).

##  Installation

Install the latest development version from [GitHub](https://github.com/rauschenberger/corila):

``` r

#install.packages("remotes")

remotes::install_github("rauschenberger/corila")

```

## Usage

Use the function [`cv.corila`](https://rauschenberger.github.io/corila/reference/cv.corila.html) to model an outcome (`n`-dimensional vector _y_) based on many predictors (`n x p` matrix _X_) that are structured by groups (e.g., `p`-dimensional vector `group`) and potentially split into primary and auxiliary predictors (`p`-dimensional vector `primary`). See the [vignette](https://rauschenberger.github.io/corila/articles/vignette.html) for detailed examples.

``` r

library(corila)

#load(toydata)

object <- cv.corila(x = x_train, y = y_train, group = group, primary = primary)

coef(object)

predict(object, newx = x_test)

```

## Reference

Armin Rauschenberger 

[![AR](https://info.orcid.org/wp-content/uploads/2019/11/orcid_16x16.png)](https://orcid.org/0000-0001-6498-4801)

(2026).

"Sparse modelling with grouped and correlated features allowing for privileged information".

*Manuscript in preparation*.

(Presented at [SIS-FENStatS](https://sis2026.sis-statistica.it/) in Rome, Italy, on 25 June 2026.)

## Disclaimer

This public repository is on a personal GitHub account, but it has private pull mirrors on two institutional GitLab instances (see [LIH](https://git.lih.lu/arauschenberger/corila) and [LCSB](https://gitlab.com/uniluxembourg/Personalfolders/armin.rauschenberger/corila)).

Large-language models (mainly Claude Sonnet 4.6 and GTP-5.4) were used for reviewing R code and documentation and for adapting configuration files (`.yaml`).

**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). This R package is distributed under a [GPL 3 license](LICENSE.md).