Seagull: lasso, group lasso and sparse-group lasso regularization for linear regression models via proximal gradient descent

BACKGROUND: Statistical analyses of biological problems in life sciences often lead to high-dimensional linear models. To solve the corresponding system of equations, penalization approaches are often the methods of choice. They are especially useful in case of multicollinearity, which appears if th...

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Detalles Bibliográficos
Autores principales: Klosa, Jan, Simon, Noah, Westermark, Pål Olof, Liebscher, Volkmar, Wittenburg, Dörte
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2020
Materias:
Software
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7493359/
https://www.ncbi.nlm.nih.gov/pubmed/32933477
http://dx.doi.org/10.1186/s12859-020-03725-w

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7493359/
https://www.ncbi.nlm.nih.gov/pubmed/32933477
http://dx.doi.org/10.1186/s12859-020-03725-w

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