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penalized: A MATLAB toolbox for fitting generalized linear models with penalties

McIlhagga, William H.
Publication Date
2016-08-28
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Keywords
Generalized linear models, Penalized regression, LASSO, MATLAB
Rights
© 2016 McIlhagga WH. This work is licensed under a Creative Commons Attribution Licence (http://creativecommons.org/licenses/by/3.0/)
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Peer-Reviewed
Yes
Open Access status
openAccess
Accepted for publication
2015-08-07
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Life Sciences Publications
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Abstract
penalized is a exible, extensible, and e cient MATLAB toolbox for penalized maximum likelihood. penalized allows you to t a generalized linear model (gaussian, logistic, poisson, or multinomial) using any of ten provided penalties, or none. The toolbox can be extended by creating new maximum likelihood models or new penalties. The toolbox also includes routines for cross-validation and plotting.
URI
http://hdl.handle.net/10454/10882
Version
Accepted manuscript
Citation
McIlhagga WH (2016) penalized: A MATLAB toolbox for fitting generalized linear models with penalties. Journal of Statistical Software. 72(6).
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Link to Version of Record
https://doi.org/10.18637/jss.v072.i06
Type
Article
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